RFID simulation An rfid anti collision algorithm with dynamic condensation and ordering binary tree An rfid anti collision algorithm with dynamic condensation and ordering binary tree An rfid anti collision algorithm with dynamic condensation and ordering binary tree
Computer Communications 36 (2013) 1754–1767 Contents lists available at ScienceDirect Computer Communications journal homepage: www.elsevier.com/locate/comcom An RFID anti-collision algorithm with dynamic condensation and ordering binary tree Yuan-Cheng Lai ⇑, Ling-Yen Hsiao, Bor-Shen Lin Department of Information Management, National Taiwan University of Science and Technology, No 43, Sec 4, Keelung Road, Taipei, Taiwan a r t i c l e i n f o Article history: Received 26 February 2013 Received in revised form 20 July 2013 Accepted September 2013 Available online 11 September 2013 Keywords: RFID Anti-collision algorithm Blocking algorithm Condensation a b s t r a c t In many RFID applications, the reader repeatedly identifies the same staying tags Existing anti-collision protocols can rapidly identify the staying tags by remembering the order in which the tags were recognized in the previous identification process This paper proposes a novel protocol, dynamic blocking adaptive binary splitting (DBA), based on the blocking mechanism, which prevents the newly-arriving tags from colliding with the staying tags Moreover, DBA utilizes a dynamic condensation technique to reduce the number of idle slots produced when recognized tags leave Following the condensation process, multiple staying tags may be required to share the same slot, and thus may cause collisions among them Accordingly, an efficient ordering binary tree mechanism is proposed to split the collided tags deterministically according to the order in which they were recognized The analytical and simulation results show that DBA consistently outperforms previous algorithms in all of the considered environments Ó 2013 Elsevier B.V All rights reserved Introduction Radio frequency identification (RFID) technology enables objects to be identified more rapidly and conveniently than traditional bar-code mechanisms In general, an RFID system consists of a reader1 and multiple tags, which communicate with one another over wireless channels Each tag has a unique identification number (UID), and thus the reader is able to identify all of the tags located within its neighborhood To identify the tags, the reader emits a trigger signal and then waits for the tags to respond However, if multiple tags transmit their UIDs simultaneously, their signals collide at the reader and thus the reader is unable to identify any of the tags and the collided tags must retransmit their UIDs The collisions not only delay the identification process but also waste the available bandwidth Consequently, in improving the performance of RFID systems, it is essential to design efficient anti-collision schemes Broadly speaking, existing anti-collision algorithms can be classified as either aloha-based [1–9] or tree-based [10–17] Alohabased algorithms estimate the number of unidentified tags within the interrogation zone of the reader and then allocate an appropriate number of slots such that the risk of collisions is reduced By contrast, tree-based algorithms, e.g., binary tree (BT) [10–13] and query tree (QT) [14–17], continually divide the collided tags into ⇑ Corresponding author E-mail address: laiyc@cs.ntust.edu.tw (Y.-C Lai) The reader is formally called as the read/write device (RWD) because the data in the RFID system are transmitted in both directions However, this paper uses the reader because most previous studies use this term 0140-3664/$ - see front matter Ó 2013 Elsevier B.V All rights reserved http://dx.doi.org/10.1016/j.comcom.2013.09.001 two subsets until each set contains at most one tag In general, aloha-based algorithms provide an effective means of reducing collisions at the beginning of the tag identification process, while tree-based algorithms are effective in avoiding the starvation problem [18], in which a specific tag is not identified for a long time In many RFID applications, the reader repeatedly identifies the same tags since they not move out of the interrogation zone between one identification process and the next, i.e., conducting roll calls during a session or monitoring audiences during a show In general, if the anti-collision algorithm can keep track of all the tags recognized in the previous identification process (i.e., in the previous frame), many collisions in the current identification process (i.e., the current frame) can be avoided and the identification process completed more rapidly as a result The adaptive binary splitting (ABS) algorithm [18,19] and adaptive query splitting (AQS) [18,20] algorithm, modified from the BT and QT schemes, respectively, both utilize this approach to improve the efficiency of the identification process In both algorithms, the reader asks the tags already recognized in the previous frame to transmit their UIDs using individually-assigned slots such that collisions among them are avoided However, while both algorithms avoid collisions among the tags which stay within the range between successive identification processes (referred to henceforth as staying tags), they not prevent collisions between the staying tags and newly-arriving tags since the latter are allowed to transmit their UIDs using the same set of slots allocated to the recognized tags To resolve this problem, Lai and Lin proposed a single resolution blocking (SRB) algorithm [21], in which the transmission of Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 the staying tags and the newly-arriving tags were constrained to different slots; thereby preventing collisions between them As a result, a lot of collisions can be circumvented, which speeds up the identification process In a later study, Lai and Lin proposed a pair resolution blocking (PRB) algorithm [22], in which the time required to re-identify the recognized tags was halved by using a pair resolution technique to couple the tags identified in the previous frame However, the PRB algorithm becomes unreliable when channel errors prevent the reader from decoding the signals of one or more of the tags In such a situation, PRB misinterprets the decoding failure as a collision between two staying tags, and yields an incorrect recognition of the tag UIDs as a result Although the SRB algorithm reduces the number of collisions by assigning different ranges of slots to the previously recognized tags and the newly-arriving tags, respectively, blocking algorithms such as SRB tend to be wasteful of the slots reserved for the recognized tags Specifically, slots may be reserved for recognized tags which subsequently move out of the interrogation zone before the following identification frame As a result, the slots are left idle Accordingly, the present study proposes an enhanced form of the SRB algorithm, designated as dynamic blocking ABS (DBA) based on a dynamic condensation technique for reducing idle slots and an ordering binary tree mechanism for collision resolution The dynamic condensation scheme adjusts the number of slots reserved for recognized tags dynamically in accordance with the estimated number of staying tags That is, when a greater number of tags are expected to move out of interrogation zone, fewer slots are reserved for the recognized tags in the following frame, and vice versa However, reducing the number of slots increases the risk of collisions among the staying tags Therefore, an ordering binary tree scheme based on the order in which the tags were identified in the previous frame is used to split the collided tags continuously into two subsets such that the collisions can be rapidly resolved The remainder of this paper is organized as follows: Section reviews the BT, ABS and SRB algorithms Section describes the overall concept and detailed operations of DBA Section presents a formal analysis of the identification delays in the BT, ABS, SRB and DBA algorithms Section compares the performance of DBA with that of ABS and SRB using both analytical and numerical methods, and describes the additional cost of DBA Finally, Section presents some brief concluding remarks Related work This section reviews the basic operations of the BT, ABS and SRB algorithms To facilitate the discussions, the following terms are first defined Frame: An identification process comprising multiple slots of interaction between the reader and the tags for the purpose of identifying all of the tag UIDs Let fi denote the i-th frame Slot: A cycle in which the tags transmit their UIDs to the reader and the reader responds with a feedback message of collision, readable, or idle, if multiple tags, one tag or no tag transmit their UID(s), respectively Let si,j be the j-th slot in the i-th frame Arriving tags in i-th frame: The tags not appear in fi-1 , but appear in fi Staying tags in i-th frame: The tags appear in fi-1 and also appear in fi Leaving tags in i-th frame: The tags appear in fi-1 , but disappear in fi 1755 Possible tags in i-th frame: The tags appear and are recognized in fi-1 , and are likely to appear in fi also Possible tags are the combination of staying tags and leaving tags On identification process, the reader and tags must write some information into memory to maintain their states For simplicity, previous studies all made several assumptions as follows (1) All operations in devices are perfectly correct (2) The time and power consumption of these operations are ignored (3) The information maintained by tags will be preserved until it is re-initialized or the power is exhausted 2.1 Binary tree (BT) algorithm The BT anti-collision algorithm uses a binary random number to divide the collided tags Every tag maintains a counter, which indicates the order in which it will be identified among all the unrecognized tags and whose value is initialized to zero Only those tags with a counter value of zero can transmit their UIDs to the reader When a collision slot appears, each of the collided tags sets its counter to a random binary number Hence, the collided tags can be divided into two subsets The reader also has a counter to keep track of the maximal value among the counters of all the tags to determine when to terminate the frame That is, the counter plus one is the number of tag sets to be recognized Once the counter falls below zero, there are no more tags to be identified and thus the current frame terminates Fig 1(a) illustrates the BT operation for the case of four tags, A, B, C and D, which are to be identified in frame fi Initially, the four tags all have a counter value of zero and therefore transmit their UIDs in the first slot, si,1 Following the resulting collision, each of the collided tags randomly sets its counter to either zero or one such that the four tags are split into two subsets Assume that tags A and D select and form the first subset while tags B and C select and form the second subset Since A and D have a counter value of zero, they are permitted to transmit their UIDs in the next slot, i.e., si,2 In the slot si,2, for example, both A and D transmit their UIDs and a collision occurs, which fails to be resolved if both tags set their counters randomly as one, and further causes the idle slot si,3 and the collision slot si,4 The collision in the slot si,4 is then resolved successfully by selecting different counter values for the tags A and D, and thus they are respectively identified in the readable slots si,5 and si,6 Fig 1(b) shows the slot-by-slot details of the BT operation, including the counter values of the reader and tags, the tags which transmit their UIDs, and the feedback message provided by the reader 2.2 Adaptive binary splitting (ABS) algorithm The ABS algorithm, modified from BT, allows each tag recognized in the previous frame to remember the order in which it transmit its UID among all tags As a result, the transmission of the staying tag will not collide with each other in the current frame, leading that many unnecessary collisions can be avoided Importantly, once the frame is terminated, each tag remembers its own ASC while the reader remembers the TSC The ASCs of the recognized tags represent the order in which the tags were successfully identified in the frame and should lie within the range of to TSC without duplication Since the ASCs have different values, they can be used in the following frame to prevent collisions among the staying tags Meanwhile, the arriving tags in the following frame can initialize their ASCs to a random number in the range of to TSC according to the TSC carried to the tags in a start 1756 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 si,1 si,2 si,7 0 si,3 si,8 si,4 si,9 Readable Idle si,5 si,6 si,10 si,11 Tag A Tag D Tag B Tag C Collision (a) Application of binary tree algorithm in frame fi Slot 10 11 12 Reader 2 1 -1 Counter value Tag A Tag B Tag C 0 0 1 2 1 2 1 0 1 0 Tag D 0 1 Responding tag A,B,C,D A,D A,D A D B,C B,C B C Feedback message Collision Collision Idle Collision Readable Readable Collision Idle Collision Readable Readable Terminate (b) Slot-by-slot binary tree procedure in frame fi Fig Illustrative example of binary tree anti-collision algorithm command sent by the reader Through sharing the slots between the staying tags and the arriving tags, ABS can reduce the idle slots due to the leaving tags at the cost of possible collisions between the staying tags and the arriving tags Fig shows the detailed operation of the ABS algorithm in two successive frames, i.e., fi and fi+1 Note that an assumption is made that no tags exist in frame fi1 As shown in Fig 2(a), the ABS procedure in frame fi, is similar to that in Fig 1(b) for the BT algorithm When frame fi is terminated, tags A, B, C and D remember their ASCs as 0, 2, and 1, respectively, since they were identified in the order of A(0)–D(1)–B(2)–C(3) In addition, the reader remembers TSC as which is the highest value of the ASCs among the four tags In frame fi+1, assume that tags C and D move out of the reader’s interrogation zone, while two new tags, E and F, arrive (see Fig 2(b)) As described above, newly-arriving tags select a random number from to TSC as their ASCs Suppose that in the present example, tags E and F select ASC values of and 2, respectively Thus, in the first slot of frame fi+1, i.e., si+1,1, the transmissions of tags A and E collide, prompting the two tags to adjust their ASCs by adding a random binary number Suppose that tag A chooses and tag E selects Consequently, the reader successfully identifies tags A and E in slots si+1,2 and si+1,3, respectively (see Fig 2(c)) A similar procedure is performed for tags B and F; resulting in their successful identification in slots si+1,9 and si+1,8, respectively 2.3 Single resolution blocking (SRB) algorithm Although the ABS algorithm prevents collisions among the staying tags, many collisions may still occur between the newly-arriving tags and the staying tags Accordingly, Lai and Lin proposed a single resolution blocking (SRB) algorithm [21], in which separate slots were allocated to the arriving tags and the staying tags, respectively Specifically, in SRB each tag identifies itself as a staying tag or an arriving tag by comparing its reader’s ID in the previous frame with the reader’s ID broadcasted by the reader at the beginning of the current frame All of the staying tags keep the original ASCs recorded in the previous frame while all of the arriving tags initialize their ASCs to a random number in the range of TSC + to an extended TSC, i.e., TSCEXT SRB will determine an appropriate value of TSCEXT for the following frame based on the number of arriving tags in the present frame In this way, SRB not only avoids collisions among the staying tags (with unique ASCs ranging from to TSC), but also prevents collisions between the staying tags and the newly-arriving tags (with randomly selected ASCs in the range of TSC + to TSCEXT) As in ABS, SRB also maintains two counters for each tag (i.e., PSC and ASC) and two counters for the reader (i.e., PSC and TSC) The operations of these counters are the same in both algorithms with the exception that SRB, being a blocking algorithm, uses additional parameters to maintain separate slots for the staying tags and the arriving tags, respectively, i.e., rRID and tRID: The reader stores its unique ID, denoted as rRID, while each tag also stores the reader’s ID, denoted as tRID ArrNum: The reader uses this counter to record the number of newly-arriving tags in each frame ANEst: The reader uses the exponential average of ArrNum to estimate the number of newly-arriving tags in the following frame TSCEXT: The reader maintains this counter to represent the maximum index of slots initially reserved for possible tags (i.e., both staying and newly-arriving) at the start of each frame That is, slot numbers from to TSCEXT are reserved, where slots in the range of to TSC are used by staying tags while slots in the range of TSC + to TSCEXT are used by arriving tags For illustration purposes, assume that SRB is used to perform the identification process for the scenario shown in Fig for frame fi+1 The tree representations for the staying and newly-arriving tags are shown in Fig 3(a), while the detailed operations of the 1757 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 ASC value Slot 10 11 12 TSC PSC 2 2 3 3 0 0 2 2 Tag A Tag B Tag C Tag D 0 0 2 2 2 2 2 3 0 1 Responding tag Feedback message A,B,C,D A,D Collision Collision Idle Collision Readable Readable Collision Idle Collision Readable Readable Terminate A,D A D B,C B,C B C (a) Slot-by-slot ABS procedure in frame fi si+1,1 si+1,4 si+1,2 Tag D leaves si+1,3 Tag A si+1,10 si+1,5 Tag C leaves si+1,7 si+1,6 Tag E si+1,8 Readable Idle si+1,9 Tag F Collision Tag B (b) Application of ABS algorithm in frame fi+1 TSC Slot 10 11 Reader 4 4 4 ASC value PSC 0 2 2 4 Tag A Tag B Tag E Tag F 0 3 3 3 1 3 3 2 Responding tag Feedback message A,E A E Collision Readable Readable Idle Collision Idle Collision Readable Readable Idle Terminate B,F B,F F B (c) Slot-by-slot ABS procedure in frame fi+1 Fig Illustrative example of ABS anti-collision algorithm SRB algorithm are shown in Fig 3(b) Assuming that the number of newly-arriving tags is estimated to be 2, and thus TSCEXT is set equal to + Assume that in randomly setting their ASCs between TSC + and TSCEXT, both newly-arriving tags (E and F) select a value of Two idle slots exist among the first four slots since tags C and D leave Furthermore, since tags E and F both have the same value of ASC, a collision occurs in slot si+1,5 Thus, the two tags are finally identified in slots si+1,6 and si+1,7, respectively Comparing Figs and 2, it is seen that SRB eliminates the risk of collisions between the staying tags and the arriving tags, and therefore is able to produce fewer collision slots blocking ABS (DBA) algorithm based on a dynamic condensation mechanism and an ordering binary tree (OBT) collision resolution scheme In the proposed approach, the dynamic condensation mechanism adaptively adjusts the number of slots (referred to as condensed slots) in accordance with the estimated number of staying tags, rather than reserving a slot for each possible tag However, since the condensation process may result in some condensed slots being shared by multiple tags, collisions may occur among the staying tags Accordingly, the OBT scheme divides the collided tags deterministically into two subsets in accordance with their ASC values remembered from the previous frame in order to resolve the collisions in a quick and efficient manner Dynamic blocking ABS (DBA) algorithm 3.1 Dynamic condensation mechanism In the SRB algorithm, the staying tags and arriving tags are assigned to the slots in different ranges in order to prevent collisions between them However, SRB reserves a slot for each possible tag; resulting in a few idle slots if some of these tags actually leave To minimize such waste, the present study proposes a dynamic Fig illustrates the basic concept of the dynamic condensation mechanism Assume that there exist a total of n possible tags with ASC values in the range of to n Assume also that the number of condensed slots is denoted as m In accordance with the 1758 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 Blocking Mechanism si+1,2 si+1,1 Tag D leaves Tag A si+1,4 si+1,3 si+1,5 Tag C leaves Tag B si+1,8 si+1,6 si+1,7 Tag E Tag F At identifying staying tags Readable No arriving tag selects this slot Idle Collision At identifying arriving tags (a) Application of SRB algorithm in frame fi+1 ASC value Slot TSC PSC 5 4 4 1 2 4 Tag A Tag B Tag E Tag F 2 4 3 2 4 3 3 Responding tag Feedback message A Readable Idle Readable Idle Collision Readable Readable Idle Terminate B E,F E F (b) Slot-by-slot SRB procedure in frame fi+1 Fig Illustrative example of SRB anti-collision algorithm Possible tags ASC Condensed ASC 10 11 12 13 14 15 16 17 Condensed slots Fig Basic concept of dynamic condensation mechanism dynamic condensation mechanism, the n possible tags are partitioned equally into m groups and each group of tags uses the same condensed slot to transmit their UIDs Since the possible tags are partitioned equally, each group contains n/m tags in average Thus, each tag can determine the condensed slot to which it belongs simply by referencing its ASC, i.e., ASC/(n/m) Since the result of the division process may not be an integer, the floor function bASC=ðn=mÞc is applied Consider a hypothetical example in which n = 18 and m = In this case, the possible tags with ASC values of 0–3, 4–7, 8–10, 11–14 and 15–17 are assigned to the condensed slots 0, 1, 2, and 4, respectively Since there may be some tags leaving, only a few tags among the possible tags stay in the current frame and can transmit using the assigned slots In general, implementing the dynamic condensation mechanism requires the resolution of two problems, namely determining an appropriate mapping of the staying tags to the condensed slots (see Fig 4) and correctly estimating the number of staying tags In practice, the number of staying tags is heavily dependent on the number of possible tags Thus, the actual number of staying tags may vary significantly from one frame to another, and is difficult to estimate as a result However, a detailed investigation shows that the staying ratio, i.e., the number of staying tags divided by the number of possible tags, generally remains stable from one frame to the next Thus, DBA uses an exponential averaging method to estimate the staying ratio Specifically, the estimated staying ratio in frame i, denoted as SREsti, is estimated as SREsti ẳ v SRi1 ỵ v Þ SREsti1 , where v is the exponential weight, while SRi1 and SREsti1 are the actual and estimated staying ratios in frame fi1, respectively Having determined the estimated staying ratio, the estimated number of staying tags is then computed as SREst n, where n is the number of possible tags Intuitively, it seems reasonable to expect that the number of condensed slots should be set equal to the estimated number of staying tags However, this approach does not lead to the optimal identification efficiency since the OBT scheme can resolve the collisions among the staying tags very effectively Thus, for any Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 SREst Optimal condensation ratio 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 SREst (a) Optimal condensation ratio vs SREst 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1759 Optimal condensation ratio 0.09 0.17 0.25 0.5 0.5 0.5 0.5 1 (b) Simplified optimal mapping table Fig Mapping of optimal condensation ratio vs estimated staying ratio estimated staying ratio, it is necessary to establish the optimal condensation ratio which minimizes the overall identification delay Fig shows the variation of the optimal condensation ratio with the staying ratio Note that the results are obtained using a binary search method based on values of the estimated staying ratio in the range of 0–1 (in incremental steps of 0.01) and identification delay is computed using the analytical method presented in (8) of Section It is observed that the optimal condensation ratio varies with a ladder-like characteristic as the value of SREst is increased In implementing the DBA algorithm proposed in this study, the results presented in Fig 5(a) are listed as 101 entries in a table mapping the estimated staying ratio to the optimal condensation ratio, and this table is then stored at the reader Fig 5(b) shows a simplified version of the table for SREst units of 0.1 Having computed SREst, the reader locates the nearest staying ratio within the table and retrieves the corresponding optimal condensation ratio The appropriate number of condensed slots, m, is determined by multiplying the optimal condensation ratio by the total number of possible tags 3.2 Ordering binary tree mechanism Due to the condensation of the slots, the risk of collisions among the staying tags is increased since the condensed slots may be shared by multiple possible tags The collisions can be solved using the traditional BT approach However, the OBT mechanism proposed in this study resolves the collisions in a more efficient manner by splitting the collided staying tags deterministically in accordance with their unique ASC values Specifically, given a collision among the staying tags with ASCs ranging from x to y, OBT divides the collided tags into two groups, namely one group containing the tags with ASCs ranging from x to bx ỵ yị=2c and another group containing the tags with ASCs ranging from bx ỵ yị=2c ỵ to y This deterministic partitioning approach results in a faster separation of the collided staying tags than the random partitioning approach used by BT As a result, the overall identification delay is effectively reduced To achieve the deterministic partitioning of the collided tags in a distributed manner, OBT must maintain some additional parameters When a collision occurs, each tag involved in the collision should use its original ASC value in the previous frame to determine whether it belongs to the first group or the second group However, the value of the ASC is initially condensed in the dynamic condensation process and then subsequently updated during the identification procedure in the ongoing frame Thus, in DBA, each tag not only maintains the ASC for the current frame like SRB, but also records the original ASC (denoted as OASC here) which is the final value of ASC of the tag in the previous frame and remains fixed during the current frame Meanwhile, it maintains two additional parameters, GL and GH, which are set equal to the lowest and highest OASCs, respectively, among all the tags within the group to which it belongs Let GM be the middle of the two parameters, i.e., GM ẳ bGL ỵ GHị=2c In the event of a collision, a collided tag with an OASC value less than or equal to GM retains its ASC value and adjusts its GH parameter to GM Conversely, a collided tag with an OASC value larger than GM increases its ASC by one and adjusts its GL to GM + Thus, the collided tags can be split into two groups based on OASC, GL and GH in a distributed manner Fig illustrates the detailed operations of the OBT mechanism Assume that eight staying tags with OASC counter values of 0–7 (i.e., the order recognized in the previous frame) are assigned to a single condensed slot and initialize their ASCs to Thus, in the first slot of the frame, i.e., si+1,0, all of the tags transmit their UIDs to the reader simultaneously To resolve the resulting collision, the tags partition themselves into two groups by comparing their OASC values with the GM value (equal to in the present example) The tags with OASCs in the range of 0–3 retain their ASC values (i.e., ASC = 0), while those with OASCs in the range of 4–7 increase their ASC by one (i.e., ASC = 1) The values of GL or GH for each tag are then adjusted accordingly Thus, the collided tags are split into two groups, i.e., one group containing tags with ASC = and a second group containing tags with ASC = The splitting procedure is repeated iteratively in this way until all of the collided tags are resolved 3.3 DBA procedure In both SRB and DBA, each tag must have the ability to determine whether it is a staying tag or an arriving tag In SRB, this is achieved by means of the reader’s ID only However, this approach may cause confusion when a tag leaves the interrogation zone of the reader and then re-enters the interrogation zone several frames later without entering the interrogation zone of another reader in the meantime Since the value of tRID is unchanged in this case, the tag interprets itself as a staying tag However, the reader should in fact regard this tag as a newly-arriving tag because the reader did not recognize the tag in the previous frame Thus this tag will possibly collide with the actual staying tag in the current frame, leading to a wrong interpretation DBA resolves this problem by using both the reader ID and a frame number parameter (tFN) to distinguish the staying tags from the arriving tags In the proposed approach, each tag sets its tFN to the current frame number when it has been recognized In a later frame, the tag compares its tFN with the current frame number received from the reader, i.e., rFN If tFN + is equal to rFN, the tag infers that it was recognized in the last frame, and therefore identifies itself to be a staying tag However, if the tag leaves the interrogation zone of the reader and then returns in a later frame without entering the interrogation 1760 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 GL=0 Si+1,0 OASC=0 GL=0 Si+1,1 OASC=0 OASC=1 OASC=0 OASC=1 OASC=1 ASC=0 ASC=1 Si+1,3 OASC=0 OASC=2 ASC=0 GL=0 GH=1 ASC=0 Si+1,2 GH=7 ASC=0 OASC=1 OASC=2 OASC=3 GH=3 OASC=3 GL=2 GH=3 ASC=1 OASC=2 OASC=3 GL=2 GH=3 ASC=2 OASC=2 OASC=3 OASC=4 GL=4 OASC=4 GL=4 OASC=4 GL=4 OASC=4 OASC=5 OASC=6 ASC=1 OASC=5 OASC=6 ASC=2 OASC=5 OASC=6 ASC=3 OASC=5 OASC=6 OASC=7 GH=7 OASC=7 GH=7 OASC=7 GH=7 OASC=7 Fig Use of OBT scheme in resolving collisions among staying tags zone of another reader in the meantime, the value of tFN + is not equal to rFN Thus, the tag interprets itself as an arriving tag even though its tRID value is equal to rRID As in the SRB algorithm, DBA uses a blocking mechanism to prevent collisions between arriving tags and staying tags Consequently, it inherits all of the SRB parameters, i.e., PSC, ASC, TSC, TSCEXT, tRID, rRID, ArrNum and ANEst (see Section 2.3) Also DBA maintains the following additional parameters: rFN and tFN: The frame numbers stored in the reader and tag, respectively StayNum: A parameter used by the reader to count the number of staying tags SREst: The estimated staying ratio calculated by the reader based on the exponential average of the actual SRs in earlier frames SR and CR: The staying ratio (SR) and condensation ratio (CR) calculated by the reader when applying the dynamic condensation mechanism OASC, GL and GH: Parameters maintained by the tags when applying OBT mechanism Fig presents the pseudo code of the DBA algorithm Note that Fig 7(a) presents the pseudo code for the reader operations, while Fig 7(b) presents that for the tag operations At the beginning of each frame, the reader calculates SREst, CR, the new condensed TSC and TSCEXT in accordance with the staying ratio (SR) and the number of arriving tags (ArrNum) calculated in the previous frame (see lines 7, 8, and 10 in Fig 7(a)) The reader then transmits a start command containing TSC, TSCEXT, CR, rRID, and rFN to all of the tags within interrogation zone (see line 14) On receiving this command, each tag compares the received rRID and rFN values with their own tRID and tFN values If either of the values does not match, the tag interprets itself as an arriving tag Thus, it set its ASC to a random number in the range of TSC + to TSCEXT (see line in Fig 7(b)) and then updates its tRID and tFN counters once it has been successfully identified (see lines 34–35 in Fig 7(b)) If the pair (tRID, tFN) equals the received pair (rRID, rFN), the tag interprets itself as a staying tag, and already has an appropriate ASC determined in the previous frame In the dynamic condensation procedure, the tag condenses this ASC as bASC CRc in order to determine the condensed slot in which it should attempt to transmit its UID Additionally, the tag sets its GL and GH counters to the lowest and highest OASCs in the group, respectively, for the purpose of resolving collisions using OBT procedure In the event of a collision among the staying tags, OBT is applied to resolve the collision using the procedures described in lines 25 to 31 in Fig 7(a) Note that the manipulations of the PSC and TSC counters in the reader and tags are very similar to those in SRB, and thus a discussion of the related procedures in Fig 7(a) and (b) is deliberately omitted here 3.4 Illustrative example of DBA procedure Fig shows the DBA identification process in frame fi+1 for the example considered in Fig involving two staying tags (A and B) and two arriving tags (E and F) Assume that the optimal condensation ratio, CR, corresponding to the estimated staying ratio, SREst, is found from the mapping table to have a value of 0.5 Furthermore, assume that the estimated number of arriving tags, ANEst, is equal to At the beginning of frame fi+1, the reader issues a start command containing TSC ¼ b3 0:5c ẳ 1, TSCEXT ẳ TSC ỵd0:88 2e ẳ 3, CR = 0.5, rRID and rFN to all four tags After receiving this command, each tag checks whether it is a staying tag or not by comparing its tRID and tFN values with those received from the reader The staying tags, i.e., A and B, then condense their ASCs from and to and 1, respectively, by applying the condensation ratio (i.e., CR = 0.5) The successful identification of tags A and B requires only two slots, si+1,1 and si+1,2, because in this case the two tags are assigned to different slots in accordance with their new ASCs following condensation, and thus no collision occurs between them Comparing the results obtained using the DBA algorithm with those obtained using SRB (see Fig 3(a)), it is found that the dynamic condensation mechanism results in the saving of the two idle slots generated by leaving tags C and D, respectively Regarding the arriving tags, E and F set their ASCs to random numbers in the range of TSC + = to TSCEXT = Assume that both tags set their ASC to a value of Thus, arriving tags E and F 1761 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 /*Dynamic Blocking ABS Reader Operation*/ PSC᧹0 PrevTSC᧹TSC if TSC᧹NULL or TSC᧹᧩1 then TSC ᧹ end if ANEst᧹uArrNum᧧(1᧩u)ArrEst SREst᧹vSR᧧(1᧩v)SREst CR᧹check table(SREst) TSC᧹TSC × CR TSCEXT᧹TSC᧧max(1,⎡0.88ANEst⎤) ArrNum᧹0 StayNum᧹0 rFN᧹rFN᧧1 Transmit the command starting a frame with TSC, TSCEXT, CR, rRID, rFN 15 TSC᧹TSCEXT 16 while PSC ≤ TSC 17 Receive tag responses and check signals 18 if tag collision then 19 TSC᧹TSC᧧1 20 f᧹collision 21 else if only a tag response then 22 if IsNew(tag) then 23 ArrNum᧹ArrNum᧧1 24 else 25 StayNum᧹StayNum᧧1; 26 end if 27 Store the tag ID 28 PSC᧹PSC᧧1 29 f᧹readable 30 else if no tag response then 31 TSC᧹TSC᧩1 32 f᧹idle 33 end if 34 Transmit feedback f 35 end while 36 StayR᧹StayNum/(PrevTSC᧧1) 37 Transmit the command terminating a frame 10 11 12 13 14 /* Dynamic Blocking ABS Tag Operation*/ Receive the command starting a frame with readers TSC, TSCEXT, CR, rRID, rFN tFN᧹tFN+1 OASC᧹−1 PSC᧹0 /*Compute the adaptive value for its ASC */ if tRIDำ rRID or tFNำ rFN or tRID᧹NULL or tFN᧹NULL then ASC᧹random number from TSC᧧1 to TSCEXT end if else 10 OASC᧹ASC 11 ASC᧹⎣ASC × CR⎦ 12 GL᧹⎡ASC ⁄ CR⎤ 13 GH᧹⎡(ASC+1) ⁄ CR⎤ −1 14 end if 15 /* Process PSC and ASC for transmission */ 16 while PSC ≤ ASC 17 if PSC᧹ASC then 18 Transmit ID 19 Receive feedback f from the reader 20 if f᧹collision then 21 if tRIDำ rRID or tFNำ rFN or tRID᧹NULL then 22 Select a binary value i randomly 23 ASC᧹ASC᧧i 24 else 25 GM ᧹⎣(GL + GH) ⁄ 2⎦ 26 if OASC ≤ GM then 27 GH ᧹ GM 28 else 29 ASC᧹ASC᧧1 30 GL ᧹ GM+1 31 end if 32 else 33 PSC᧹PSC + 34 tRID=rRID 35 tFN=rFN 36 end if 37 else if PSC᧸ASC then 38 receive feedback f from the reader 39 if f᧹collision then 40 ASC᧹ASC + 41 else if f᧹readable then 42 PSC᧹PSC + 43 else if f᧹idle then 44 ASC᧹ASC᧩1 45 end if 46 end if 47 end while Fig Pseudo code of DBA anti-collision algorithm collide in slot si+1,3, but are finally identified in slots si+1,4 and si+1,5, respectively, (say) following the random resolution by the conventional BT method Performance analysis This section presents a formal analysis of the average identification delay in the ABS, SRB and DBA algorithms, respectively All three algorithms are based partially on the BT scheme Thus, for convenience, the section commences by deriving the average identification delay of BT, even though the corresponding derivation is already available in previous studies [18,19] ẳ Ni ịPi P ịNi with parameters N = n and P = 1/2 Each subset is split repeatedly until the resulting sets contain either no tags or just one tag, i.e., DBT(0) and DBT(1), and require an idle slot or a readable slot, respectively Thus DBT(n) can be expressed as the following recursive function, DBT ðnÞ ¼ n X Pr i; n; 12 ½1 ỵ DBT iị ỵ DBT n iị; iẳ0 where Pri; N; Pị ẳ N i Pi PịNi ; 1ị DBT 0ị ẳ DBT 1ị ẳ 1: 4.2 ABS 4.1 BT Let the total number of slots required in a frame to identify n tags be denoted as DBT(n) At the start of the identification process, the n tags collide in the first slot and are randomly divided into two subsets containing i tags and n i tags, respectively The probability that i tags out of n tags are selected through binary random tests follows a binomial distribution B(N, P), i.e., Prði; N; PÞ Assume that n tags are recognized in the previous frame and that the numbers of arriving tags and staying tags in the current frame are denoted as a and b, respectively In ABS, an individual slot is assigned to each of the n possible tags, and thus a total of b slots are occupied by staying tags, while the remaining n b slots are empty For each of the b occupied slots, if i arriving tags select the slot, the slot will contain a total of + i tags, and thus DBT(1 + i) 1762 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 Blocking Mechanism Readable si+1,1 si+1,2 Tag A si+1,3 Tag B Tag D leaves Tag A Tag C leaves Tag B si+1,6 Idle No arriving tag selects this slot si+1,4 si+1,5 Tag E Tag F Collision Condensation-Staying tags Condensation- Leaving tags Dynamic Condensation At identifying staying tags At identifying arriving tags (a) Application of DBA mechanism in frame fi+1 TSC Slot Reader 3 4 ASC value PSC 2 4 Tag A Tag B Tag E Tag F Responding tag Feedback message 1 2 2 2 3 A B E, F E F Readable Readable Collision Readable Readable Idle Terminate (b) Slot-by-slot DBA procedure in frame fi+1 Fig Illustrative example of DBA anti-collision algorithm slots are required to achieve collision resolution using the BT scheme For each of the n b empty slots, if the slot is selected by i arriving tags, the slot will contain i tags, and therefore DBT(i) slots are required to achieve collision resolution Since each arriving tag selects any one of the n slots with an equal probability of 1/n, the probability that i out of the a arriving tags select a specific slot follows a binomial distribution B(N, P), with parameters N = a and P = 1/n Therefore, the average identification delay for ABS is given as The minimal identification delay is obtained under perfect esti^ ¼ a Thus, the optimal value of the SRB mation conditions, i.e., a identification delay, denoted as DSRB ðn; a; bÞ, is given as a X DABS n; a; bị ẳ b Pr i; a; DBT ỵ iị n iẳ0 a X ỵ n bị Pr i; a; DBT iị: n iẳ0 4.4 DBA 2ị 4.3 SRB Since SRB is a blocking algorithm, the staying tags and arriving tags are initially assigned to the slots of two separate regions, corresponding to the ranges of to TSC and TSC + to TSCEXT, respectively Assume there are n recognized tags in the previous frame Then in the current frame, the first region contains n slots allocated to n possible tags, and thus the identification delay is simply equal to n (n = TSC + here) In the second region, given an estimated ^ , the optimal number of slots number of arriving tags equal to a ^ e [21,22] Since allocated for these arriving tags is equal to d0:88a ^ e slots with equal each arriving tag selects any one of these d0:88a probability, the probability that i out of the a arriving tags select a specific slot follows a binomial distribution B(N, P), with parame^ e Therefore, the identification delay ters N = a and P ¼ 1=d0:88a of SRB is equal to Pr i; a; a X ^e DSRB n; a; bị ẳ n ỵ d0:88a iẳ0 D iị: ^ e BT d0:88a ð3Þ a X DSRB ðn; a; bÞ ẳ n ỵ d0:88ae Pr i; a; iẳ0 DBT ðiÞ: d0:88ae ð4Þ As with SRB, DBA is also a blocking algorithm, and thus the identification process is again performed on the slots in two separate regions The identification delay in the second region of the frame is the same as that for SRB However, the identification delay in the first region of the frame requires elaborate calculation Assume that m condensed slots are reserved for n possible tags, i.e., the number of possible tags for each condensed slot (denoted as k) is equal to n/m For analytical convenience, suppose that k is an integer When b staying tags are randomly selected out of n possible tags, the probability that a specific condensed slot has exactly i staying tags (out of k possible tags for this slot) is equal to n ðki Þðnk bi Þ=ðb Þ If i > 1, then i staying tags in the condensed slot collide and need to be resolved using the OBT mechanism Let DOBT(k, i) denote the number of slots required to resolve the collisions of i tags among k possible tags Therefore, the identification delay in the first region of slots, DDBA1(n, a, b), can be calculated as k X ðki Þðnk bi ị DDBA1 n; a; bị ẳ m DOBT k; iị; n bị iẳ0 where k ẳ n : m ð5Þ In accordance with the OBT operation, the i (i P 2) collided tags among the k possible tags in a condensed slot are split into two groups, namely one group containing j collided tags among bk=2c possible tags and a second group containing i j collided tags Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 among dk=2e possible tags Since the probability for such a division dk=2e is equal to ðjbk=2c Þðij Þ=ðki Þ, the total number of slots required for OBT collision resolution is given by DOBT k; iị ẳ mini;k X lị k jẳmax0;ikh ị where kl ẳ k hị j l ịij B 1 C @ ỵDOBT kl ; jị A; ỵDOBT kh ; i jị ki ị k ; kh ẳ 2k : 6ị DOBT k; 0ị ẳ DOBT k; 1ị ẳ 1: In practical applications, k is unlikely to have an integer value In this case, the m condensed slots can be divided into m1 and m2 slots, with each slot containing k1 ¼ bn=mc possible tags and k2 ¼ dn=me possible tags, respectively m1 and m2 can be obtained by solving the equations m1 þ m2 ¼ m and m1 k1 þ m2 k2 ¼ n The identification delay in the first region of the frame, DDBA1(n, a, b), can then be obtained as DDBA1 n; a; bị ẳ m1 k1 k1 nk1 X ị ị i iẳ0 bi nb ị DOBT k1 ; iị ỵ m2 k2 k2 nk2 X ị Þ i i¼0 bi ðnb Þ DOBT ðk2 ; iÞ; where k1 ẳ bn=mc and k2 ẳ dn=me: 7ị In (5) and (7), the optimal value of the identification delay, DDBA1 ðn; a; bÞ, is obtained when using the optimal value of m⁄, i.e., the value of m for a perfect estimation of the staying ratio As described in Section 3.1, after obtaining the staying ratio, the reader searches the mapping table to find the corresponding optimal value of the condensation ratio (CR) corresponding to the staying ratio (SR) as depicted in Fig 5, and m⁄ can then be obtained by n CR The optimal DBA identification delay, DDBA ðn; a; bÞ, can then be obtained as DDBA ðn; a; bị ẳ DDBA1 n; a; bị ỵ m a X Pr i; a; iẳ0 DBT iị: d0:88ae ð8Þ Simulation and performance comparison In this section, the identification performance of DBA is compared with that of ABS and SRB, respectively Note that BT is not included for comparison purposes since it identifies all of the tags from scratch in every frame In other words, it is not intended to enhance the efficiency of the re-identification procedure, and therefore inevitably achieves a much poorer performance than either ABS or SRB [20–22] Showing the results of BT will cause that the curves of ABS, SRB, and DBA shown in the figure are indistinguishable Also, currently no any aloha-based algorithm is designed for the re-identification scenario Therefore, the alohabased algorithms, including frame slotted aloha-based algorithm [1–9] and the Q-algorithm in EPCGen tags [3,25], are not compared in our simulation for the same reason above The performance of the three algorithms is evaluated in terms of three metrics, namely the number of collision slots, the number of idle slots, and the total number of slots required to identify all the tags Note that the number of readable slots is not considered since this metric is the same for all three algorithms The simulations commence by investigating the effect of the number of staying tags and arriving tags on the identification performance of the three schemes In performing the simulations, it is assumed that the staying ratio and the number of arriving tags in SRB and DBA are correctly estimated such that the optimal identification performance is obtained Let Z be the total number of tags to be identified in the frame The identification performance of each scheme in the i-th frame, fi, is then evaluated by varying the staying ratio rs and the arriving ratio ra, where rs is defined as the 1763 ratio of the number of staying tags over n and is defined as the ratio of the number of arriving tags over Z n, where n is the number of recognized tags in the (i 1)th frame In the ABS, SRB and DBA schemes, the staying ratio and the number of arriving tags are both estimated using an exponential averaging method, and are therefore dependent on the mobility of the tags Therefore, in the second series of simulations referred to [21–24], the effects of tag mobility on the identification performance of the three schemes are systematically explored As the environment in [18,21,22], the simulations consider a total of Z mobile tags located randomly within an area measuring 10 m 10 m Each tag is assigned a stationary probability which determines whether or not it moves during the period of one frame Moreover, the tag velocity is defined as the distance moved by each tag during one frame if it moves The reader is located in the center of the simulation environment and is assumed to have an interrogation zone of just m Hence, some tags enter and leave the interrogation zone as they move during the frame The initial position and direction of the tags are specified randomly within the simulation area If a tag touches the border of the simulation area, it randomly selects a new direction of travel Fig shows an example of the simulation environment with 15 mobile tags in a 10 m 10 m simulation area A reader, with m interrogation zone, is located in the center All tags move according to the stationary probability equal to 0.2 and the tag velocity equal to 1.5 m per frame In Fig 9, 12 tags move with random directions while three tags not move between two continuous frames The 12 moving tags includes tags entering, tags leaving, tags staying in, and other tags locating outside, the interrogation zone Three unmoving tags contain tag staying in the interrogation zone and tags locating outside the zone Thus, the reader has to recognize tags, including arriving tags and staying tags in the current frame Each simulation is performed over a total of 106 frames The simulations consider the effects of three specific parameters, namely the tag velocity and the stationary probability It is worthy to be mentioned that all algorithms compared in this paper are based on BT, so their performance is not affected by the tag UID distribution Thus even when the UID distribution of leaving tags is not uniformly distributed, the performance of these algorithms are not changed 5.1 Effect of arriving tags Fig 10 shows the effect of the arriving ratio, ra, on the identification performance of the three schemes given a constant staying ratio of rs = 0.5 Note that Z = 1000 and n = 500 In general, the results show that for every scheme, the identification delay increases with an increasing arriving ratio as the result of a greater number of collision slots, idle slots and total slots, respectively Fig 10(a) shows that ABS results in the greatest number of collision slots for most values of due to the large number of collisions which occur between the arriving tags and the staying tags As the value of increases, the probability of the arriving tags colliding with the staying tags also increases, and thus the performance gap between ABS and SRB and DBA, respectively, increases Of the three schemes, SRB results in the lowest number of collisions since its blocking strategy ensures that collisions are limited only to the arriving tags In the DBA algorithm, the dynamic condensation mechanism produces additional collisions among the staying tags Thus, for a given value of ra, the number of collisions in DBA is greater than that in SRB However, since the probability of collisions among the arriving tags in DBA is the same as that in SRB and the dynamic condensation procedure only generates collisions among the staying tags, the performance gap between the two schemes is independent of the arriving ratio 1764 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 Tag velocity: 1.5 m/frame Stationary Prob.: 0.2 Z = 15 Reader S Staying tag L A A Arriving tag S L S A A L Leaving tag A 10 m S L S Other tag S Tag at original location L L A Reader’s interrogation zone L A Move Path 10 m Fig An example of the simulation environment DBA ABS 700 600 600 500 500 400 300 400 300 100 100 DBA 200 200 SRB Total slots SRB Idle slots Collision slots ABS 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Ratio of arriving tags 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 2000 1800 1600 1400 1200 1000 800 600 400 200 0 Ratio of arriving tags (a) Collision (rs=0.5) (b) Idle (rs=0.5) ABS SRB DBA ABS_M SRB_M DBA_M 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Ratio of arriving tags (c) Total (rs=0.5) Fig 10 Effect of arriving ratio on identification performance of three schemes The results presented in Fig 10(b) show that SRB yields the greatest number of idle slots since the slots reserved for the leaving tags cannot be used By contrast, in DBA, the possible tags share a smaller number of condensed slots instead of monopolizing individual slots can reduce the idle slots effectively, and achieve the lowest number of idle slots The number of idle slots for both SRB and DBA increases with increasing arriving ratio because the number of extended slots allocated for the arriving tags, i.e., ^ e, also increases In ABS, on the other hand, some of the d0:88a arriving tags can utilize the idle slots released by the leaving tags so as to reduce the idle slots However, it is observed in Fig 10(b) that the number of idle slots increases slowly with increasing It is because, when there are more arriving tags, there arise more collisions inevitably which might produce extra idle slots during random resolution In addition, DBA can produce fewer idle slots than ABS It is because directly condensing the slots allocated for the possible tags in DBA is more effective on eliminating idle slots than randomly assigning the arriving tags to these slots in ABS In Fig 10(c), it is seen that SRB results in almost the same number of total slots as ABS since the number of saved collision slots is approximately equal to the number of wasted idle slots when rs = 0.5 DBA achieves the best performance of the three schemes since it reduces the number of idle slots by means of the dynamic condensation procedure while also minimizing the number of collisions by means of the blocking mechanism The curves denoted as ABS_M, SRB_M and DBA_M in Fig 10(c) indicate the analytical results obtained from the mathematical analyses of the ABS, SRB and DBA schemes in (2), (4) and (8), respectively, in Section 4, while the discrete points show the simulation results It is observed that a good agreement exists between the two sets of results for each scheme The improvements of DBA are verified successfully by both analytical formula and simulations 5.2 Effect of staying tags Fig 11 shows the effect of the staying ratio, rs, on the identification performance of the three schemes given a constant arriving ratio of = 0.5 Note that Z = 1000 and n = 500 Fig 11(a) shows that the number of collision slots in SRB is insensitive to the staying ratio since the collisions are limited to the arriving tags only By contrast, in DBA, collisions also occur among the staying tags, and 1765 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 SRB ABS DBA 500 Idle slots Collision slots 400 300 SRB DBA ABS 700 1600 600 1400 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 800 400 100 DBA_M 600 200 100 DBA SRB_M 1000 400 300 200 SRB ABS_M 1200 500 Total slots ABS 200 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Ratio of staying tags Ratio of staying tags Ratio of staying tags (a) Collision (ra=0.5) (b) Idle (ra=0.5) (c) Total (ra=0.5) Fig 11 Effect of staying ratio on identification performance of three schemes SRB ABS DBA 150 Idle slots Collision slots 200 100 50 SRB DBA ABS 350 850 300 750 250 Total slots ABS 200 150 100 0.5 1.5 2.5 Velocity 3.5 DBA 650 550 450 350 50 SRB 0.5 1.5 (a) Collision 2.5 3.5 250 0.5 1.5 2.5 Velocity Velocity (b) Idle (c) Total 3.5 Fig 12 Effect of tag velocity on identification performance of three schemes thus the number of collision slots is greater than in SRB In the ABS algorithm, the number of collision slots increases as rs increases since a greater number of staying tags are present, and thus the risk of collisions among the staying tags and the arriving tags increases As a result, ABS yields a greater number of collision slots than either SRB or DBA for most values of the staying ratio However, for low values of rs (i.e., rs < 0.2) a large number of slots are reserved for the leaving tags and can be re-used by the arriving tags, so the risk of collisions between the arriving tags and the staying tags is reduced Thus, under these particular conditions, the number of collisions in ABS is less than that in either SRB or DBA As expected, Fig 11(b) shows that the number of idle slots generally reduces as rs increases in all three schemes Of the three schemes, SRB results in the largest number of idle slots for most values of rs (i.e., rs < 0.8) since when some of the tags leave, the slots previously reserved for these slots are not re-used DBA resolves this problem using the dynamic condensation mechanism, and thus it yields the lowest number of idle slots among the three schemes However, the performance gap between SRB and DBA reduces at higher values of rs (i.e., rs P 0.8) since, when the slots allocated for the possible tags (in SRB) are highly occupied by the staying tags, further condensation procedure as applied in DBA then fails to reduce the number of idle slots any more In Fig 11(a) and (b), it is seen that the DBA curves have an irregular shape since the optimal condensation ratio has a ladder-like response to an increasing value of rs As shown in Fig 5(a), the optimal condensation ratio (i.e., CR = 1) is obtained for all values of rs greater than 0.7 Given a condensation ratio of CR = 1, the DBA algorithm reduces to the SRB scheme, and thus the number of collision slots or the number of idle slots is the same in both cases Fig 11(c) shows that the DBA algorithm results in the lowest number of total slots among the three algorithms Briefly, ABS is vulnerable due to a greater number of collision slots at large rs, while SRB is vulnerable due to a greater number of idle slots at small rs DBA effectively reduces the idle slots by dynamic condensation while efficiently resolve the collisions by OBT, and therefore gets the best of the two schemes successfully 5.3 Effect of tag velocity Fig 12 shows the effect of the tag velocity on the identification performance of the ABS, SRB and DBA schemes given a stationary probability of 0.2 and Z = 1000 As the mobility of the tags increases, the probability that they will enter or leave the reader’s interrogation zone also increases In other words, the arriving ratio increases while the staying ratio rs reduces For all three schemes, the greater number of arriving tags results in more collision slots (see Fig 12(a)), while the reduced number of staying tags results in more idle slots (see Fig 12(b)) For low values of the tag velocity (i.e., 61.5 m/frame) the SRB and DBA schemes yield a similar number of collision slots and idle slots since under low mobility conditions, the staying ratio rs increases, and thus the dynamic condensation procedure has only a limited effect However, for tag velocities greater than 1.5 m/frame, the number of staying tags becomes smaller, and thus the DBA scheme achieves fewer idle slots through condensation than SRB, at the cost of more collision slots which can be efficiently resolved by OBT The price paid by DBA is worthy considering the overall performance Fig 12(c) shows that DBA requires significantly fewer total slots than SRB at higher values of the tag velocity due to the improved efficiency of the dynamic condensation process It is also 1766 Y.-C Lai et al / Computer Communications 36 (2013) 1754–1767 SRB ABS DBA SRB ABS DBA 250 650 150 210 610 130 110 90 170 130 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 50 SRB DBA 570 530 490 90 70 50 Total slots 170 Idle slots Collision slots ABS 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 450 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Stationary Probability Stationary Probability Stationary Probability (a) Collision (b) Idle (c) Total Fig 13 Effect of stationary probability on identification performance of three schemes observed that the SRB curve approaches and then exceeds the ABS curve as the tag velocity is increased This implies that the performance benefit achieved by SRB in restricting collisions to the new arriving tags is gradually eroded (and then outweighed by) by the performance loss arising from the corresponding increase in the number of idle slots However, this tendency is mitigated by the dynamic condensation procedure performed in DBA, and thus DBA outperforms SRB as the tag mobility increases 5.4 Effect of stationary probability Fig 13 shows the effect of the stationary probability on the identification performance of the three algorithms given a constant tag velocity of 2.5 m/frame and Z = 1000 For a high value of the stationary probability, most of the tags are immobile In other words, most of the tags which are initially outside of the reader’s interrogation zone remain out of range, while most of the tags which are initially within the communication remain within range That is, given a large stationary probability, the value of reduces while that of rs increases Therefore, in all three schemes, the benefit of remembering the possible tags increases as the stationary probability increases; resulting in both a lower number of collision slots and fewer idle slots, as shown in Fig 13(a) and (b), respectively The results presented in Fig 13(a) and (b) show that SRB yields far fewer collision slots than ABS, but significantly more idle slots Meanwhile, Fig 13(c) shows that SRB requires fewer total slots than ABS to accomplish the identification procedure for values of the stationary probability greater than 0.1 For all values of the stationary probability less than 0.4, DBA yields the lowest total number of slots of the three schemes At higher values of the stationary probability, the DBA and SRB schemes require a similar number of slots since under such conditions, the performance improvement yielded by the dynamic condensation procedure is reduced 5.5 Additional cost of DBA To achieve better performance, DBA must pay some additional cost in memory and processing In a general RFID system, the reader has powerful computation capability and large memory, so the additional cost in the reader can be ignored Each tag owns memory to store some parameters for performing its algorithm, e.g PSC and ASC used in ABS and tRID used in SRB Thus, the extra parameters used in DBA, i.e., tFN, OASC, GL, GH, and GM, can be also stored in memory Although the minimal memory size of a tag is defined as bytes in ISO 18000-6 [26], many RFID tags already existing in the market provide much larger memory, e.g Alien Higgs chip and NXP UCODE G2XM chip provide 512-bit memory Therefore, the additional memory cost caused by DBA is acceptable for these tags The tag adopting DBA has slightly larger processing cost than the tag adopting SRB because of two reasons First, the tag applies dynamic condensation to obtain initial values of OASC, condensed ASC, GL, and GH only at the start of each frame Thus, the additional cost is minimal because each tag computes these values only once with time complexity O(1) at each frame Second, the tag performs OBT to solve collisions among staying tags However, the operations in OBT, including parameter comparisons and updates, are similar to those in ABS and SRB Therefore, the operations not generate additional processing overhead Conclusion In RFID systems, efficient collision resolution algorithms are necessary to minimize the time required to complete the tag identification process Accordingly, this paper has proposed a novel tree-based anti-collision algorithm designated as dynamic blocking ABS (DBA) As in the single resolution blocking (SRB) algorithm proposed by the current group in [21], DBA prevents collisions between the arriving tags and the staying tags by assigning the tags to different regions of slots In addition, a dynamic condensation mechanism is applied to reduce the number of idle slots generated when possible tags leave the reader’s interrogation zone The condensation process increases the probability of collisions among the staying tags Thus, an ordering binary tree (OBT) mechanism is proposed for resolving the resulting collisions in an efficient manner The performance improvement achieved by DBA relative to SRB is particularly significant at low values of the staying ratio due to the dynamic condensation mechanism and OBT scheme However, DBA also outperforms SRB in realistic identification environments characterized by a high tag velocity and a low stationary probability Since DBA is a blocking algorithm, its identification performance is significantly better than that of ABS at high values of the staying ratio In addition, DBA significantly outperforms 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Parameters for Air Interface Communications at 860 MHz to 960 MHz, Amendment 1: Extension with Type C and Update of Types A and B, ISO/IEC 18000-6:2004/Amd 1:(E), June 2006 ... tags and the arriving tags, and therefore is able to produce fewer collision slots blocking ABS (DBA) algorithm based on a dynamic condensation mechanism and an ordering binary tree (OBT) collision. .. proposes an enhanced form of the SRB algorithm, designated as dynamic blocking ABS (DBA) based on a dynamic condensation technique for reducing idle slots and an ordering binary tree mechanism for collision. .. example, both A and D transmit their UIDs and a collision occurs, which fails to be resolved if both tags set their counters randomly as one, and further causes the idle slot si,3 and the collision