Topology Control in Wireless Ad Hoc Networks phần 5 ppsx

5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica The CBTC protocol (2) TC protocols: 8/12  The CBTC protocol produces a connected communication graph if ρ ≤ 2π/3  The obtained communication graph is made symmetric by adding the reverse edge to every unidirectional link  A set of optimizations are also proposed, that prune energy-inefficient edges while not impairing connectivity and symmetry  Drawback: directional information required  Several variants of CBTC have been introduced [Bahramgiri et al.02][Huang et al.02] 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica Neighbor-based TC TC protocols: 9/12  Other class of TC protocols based on the k-neighbors graph, i.e. the graph in which every node is connected to its k closest neighbors  First neighbor-based TC protocol: the LINT protocol of [RamanathanRosales- Hain00]: – Basic idea: try to keep the number of neighbors of every node within a low and high threshold centered around an “optimal value” – Number of neighbors estimated overhearing control and data messages – Drawbacks: the “optimal value” is not characterized; the estimation of the number of neighbors might be inaccurate (silent neighbors are not detected); connectivity is not guaranteed  KNeigh [Blough et al.03a]: – Goal: maintain the number of physical neighbors equal to (or slightly below) k – k is chosen in such a way that the graph generated is connected w.h.p. – The graph produced is symmetric – On the average, it is 20% more energy-efficient than CBTC – Drawback: based on distance estimation; connectivity only w.h.p. 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica The optimal value of k TC protocols: 10/12 Optimal value of k for increasing n 0 1 2 3 4 5 6 7 8 9 10 10 100 1000 n k Optimal value Optimal value of k for increasing values of n (from [Blough et al. 03]) Remark: setting k = 9 guarantees connectivity w.h.p. for values of n ranging from 50 to 500 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica Sample topologies TC protocols: 11/12 Sample topologies generated in case of CTR topology control (left), and after KNeigh (center) and CBTC (right) execution. The number of nodes is n = 100 (from [Blough et al. 03]) 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica The XTC protocol TC protocols: 12/12  XTC is a very recent protocol by the same author of CBTC [WattenhoferZollinger04]  Basic idea (similar to KNeigh): – at the beginning, every node orders its neighbors (set of nodes in the maximum transmitting range) according to some criterion (e.g., link quality) – then, every node transmits its order at maximum power – based on its own order, and on the orders of its neighbors, every node determines the set of “logical” links according to a simple rule  XTC always produces a connected communication graph (provided the original graph is connected)  Drawback: no upper bound on the number of physical neighbors 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica Mobile networks Mobility: 1/10  Which is the impact of mobility on TC? – Increased message overhead: contrary to the stationary case, the protocol must be re-executed periodically in response to node mobility the “message efficiency” of the protocol is fundamental: protocols that exchange few messages to maintain the topology are needed – Non-uniform node distribution 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica Mobility models Mobility: 2/10  Impact of mobility on TC depends on the mobility pattern  Mobility models: – Random waypoint model: most widely used mobility model in the ad hoc networks community. Every node chooses uniformly at random a destination in [0,1] 2 , and moves towards it along a straight line with velocity chosen at random in [v min ,v max ]. When it reaches the destination, it rests for a time t pause , then it starts moving according to the same rule – Random direction model: nodes move with direction chosen uniformly at random in [0,2π [, and velocity chosen at random in [v min ,v max ]. After a randomly chosen time, the node chooses a new direction and velocity – Brownian motion: the node position at the next time step is chosen uniformly at random in a disk centered around the current node position 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica RWP and Random Direction Mobility Mobility: 3/10 RWP mobility (left) and Random Direction mobility (right). In case of RWP mobility, nodes tend to cross the center of the deployment region (border effect) 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica The mobile CTR Mobility: 4/10  With homogeneous topology control, message overhead is not an issue, since the nodes’ transmitting range is set at the design stage and cannot be change dynamically  However, the node spatial distribution generated by the mobility pattern could be an issue  For instance, it is known that the RWP model generates non-uniform node spatial distribution [Bettstetter et al.03]  On the other hand, the node distribution generated by random direction and Brownian mobility is very close to uniform [Blough et al.02b] 5 th ACM MobiHoc – Tokyo, May 24, 2004 Istituto di Informatica e Telem atica The mobile CTR (2) Mobility: 5/10 Node distribution generated by the RWP model with different values of the pause time (from [Blough et al.02b]) Remark: the fact that the node spatial distribution generated by RWP mobility is not uniform should be carefully considered when simulating mobile ad hoc networks . value Optimal value of k for increasing values of n (from [Blough et al. 03]) Remark: setting k = 9 guarantees connectivity w.h.p. for values of n ranging from 50 to 50 0 5 th ACM MobiHoc – Tokyo, May 24,. waypoint model: most widely used mobility model in the ad hoc networks community. Every node chooses uniformly at random a destination in [0,1] 2 , and moves towards it along a straight line with. 2π/3  The obtained communication graph is made symmetric by adding the reverse edge to every unidirectional link  A set of optimizations are also proposed, that prune energy-inefficient edges