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Cluster construction research in mobile ad hoc network

Cluster construction research in mobile ad hoc network. NTUIM92 R92725034 資管所研二 林明源 IM Graduate Lin Ming Yuan. Outline. Problem statement Previous work Cluster construction Mobility research Integer formulation for clustering Energy-efficient multicasting and wireless advantage My work.

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Cluster construction research in mobile ad hoc network

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  1. Cluster construction research in mobile ad hoc network NTUIM92 R92725034 資管所研二 林明源 IM Graduate Lin Ming Yuan

  2. Outline • Problem statement • Previous work • Cluster construction • Mobility research • Integer formulation for clustering • Energy-efficient multicasting and wireless advantage • My work

  3. Problem statement (1/2) • For specific applications like military missions, emergency response operations, electronic community communication etc, we desire to construct a cluster topology in mobile ad hoc network including following considerations： • Wireless communication advantage • Individual/Group-based mobility pattern • Cluster coordinator/manager selection (clusterhead) • Resource management and allocation in clusters • Connectivity • Stability • Reliability • Efficient routing through clusterhead

  4. Cluster member Clusterhead Gateway node Intra-Cluster link Cross-cluster link Problem statement (2/2) In the remaining slides, I will describe the issues mentioned above in detail, summary of the previous related works and methodologies and my work.

  5. Outline • Problem statement • Previous work • Cluster construction • Mobility research • Integer formulation for clustering • Energy-efficient multicasting and wireless advantage • My work

  6. Cluster construction(1/10) • A mobility-based clustering approach to support mobility management and multicast routing in mobile ad-hoc networks[international journal of network management 2001;11:387-395][Author:Beongku An, Symeon Papavassiliou ] • MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network[wireless communication and mobile computing2003;3:255-270][Author:Beongku An, Symeon Papavassiliou ] • Geomulticast: architecture and protocols for mobile ad hoc wireless networks [www.ComputerScience Web.com received 17 October 2002][Author:Beongku An, Symeon Papavassiliou ]

  7. Cluster construction(2/10) • For some location-based reasons like regional network management and resource allocation and scalability etc., we desire to partition nodes to subsets. And clustering is the method to organizes unlabeled nodes into groups by using feature vectors (such as similar mobility pattern). • High cost to reconstruct the topology and election when clusterhead move out the coverage of the cluster. • Reconstruction causes the variation of the scheduling and allocation and downsize the performance and utilization. • Stability in location and less mobility are more important. • In MHMR, the author proposed MBC approach that use a combination of both physical and logical partitions of network(ex. geographic proximity and functional relation between nodes, such as mobility pattern, etc.)

  8. Cluster construction(3/10) • From observations of the group mobile behavior, the author want to propose a Mobility-based Hybrid Multicast Routing (MHMR) which has the following three features and considerations: • Mobility-based clustering and group-based hierarchical structure • Group-based (limited) mesh structure and forwarding tree concept • Combination of proactive and reactive concepts providing low acquisition delay and low overhead • Channel access and code separation • Power control and bandwidth allocation • Mobility management

  9. MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network Cluster construction (mobility pattern)(4/10) • Relative velocity V(m,n,t) between the node m and n is defined as : • Average relative mobility M m,n,T between any pair (m,n) of nodes during time period T is defined as: • Average motion behavior of a cluster Ci is defined as: • Average relative mobility within the cluster Ci is defined as:

  10. MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network Cluster construction (heuristic)(5/10) • Step1.Mobility Information Dissemination • Each node n periodically disseminate its velocity information (V(n,ti),i=1,2…) to its neighboring nodes. • Step2.Calculating Mobility Metrics • Upon reception of neighboring nodes’ velocity information, each node calculate the relative velocity V(m,n,T) of each pair nodes and exchange periodically. • Step3.Initial Cluster Construction • Construct the set Sm includes node m and all the nodes from which node m receives mobility information. • Among the nodes of Sm the node-i with the lowest ID that satisfies the following condition: Mm,i,T < Thmob .Node i €Sm is selected as a tentative clusterhead. That is

  11. MHMR: mobility-based hybrid multicast routing protocol un mobile ad hoc wireless network Cluster construction (heuristic)(6/10) • Thmod is the mobility threshold parameter for the network stability. (random node’s mobility or group mobility) • Step4.Clustering merging • According to the step 3, a parent clusterhead can include the other child clusterheads as long as satisfying the TCH criteria and under the upper bound of the number of hops (L). • Step5.Cluster Maintenance and Reconstruction • When a node m moves into the cluster Cj and the clusterhead node n in cluster Cj still satisfies the condition : Mm,i,T < Thmob , it’s not necessary to reconstruct the cluster and elect new clusterhead. Then the node m request to clustering to node n. Otherwise node m repeats step 5 during this motion, elect new clusterhead among these nodes and reconstruct the cluster

  12. MBC approach (reference)(7/10)

  13. Cluster construction- other proposed approach(8/10) • Max-min D-cluster formation in wireless ad hoc networks[inforcom 2000] [Author:Alan D. Amis Ravi Prakash Thai, H.P.Vuong Dung T. Huynh Department of Computer Science University of Texas at Dallas] • A multicast routing protocol for ad hoc network[processing of inforcom99 784-792 March 99] [J.J. Garcai-Luna-Aceves and Ewerton L. Madruga]

  14. Max-min D-cluster formation in wireless ad hoc networks(9/10) The heuristic runs for 2d rounds of information exchange. Each node maintains two arrays, WINNER and SENDER, each of size 2d node ids: one id per round of information exchange. First round to select maximum ID as clsusterhead and second round to adjust the selected CH by minimum ID for load balance consideration.

  15. A multicast routing protocol for ad hoc network(10/10) Shared core-based multicast tree for each group and construct a mesh from different group trees. The source node transmits the traffic to the core node and downstream multicast to the tree members. New members join via group tree members or trace the neighbor to the core node (tree manager).

  16. Outline • Problem statement • Previous work • Cluster construction • Mobility research • Integer formulation for clustering • Energy-efficient multicasting and wireless advantage • My work

  17. Mobility research(1/8) • A survey of mobility model for ad hoc network research [wireless communication and mobile computing 2002;2:483-502][author: Tracy camp, Jeff Boleng, and Vanessa Davies] • ODMRP On-demand multicast Routing Protocol in Multihop Wireless Mobile Networks [Mobile Network and Application; Dec 2002;7,6;ABI/INFORM Global][Authors: Sung-Ju Lee, William Su, Mario Gerla]

  18. A survey of mobility model for ad hoc network research(2/8) • Two type of the mobility models • Independent (entity mobility model)-Entity mobility models : mobility models that represent mobile nodes whose movements are independent of each other. • Random walk mobility model (the most common) • Random waypoint mobility model (the most common) • Random direction mobility model • A boundless simulation mobility model • Gauss-Markov mobility model • A probabilistic mobility model • City section mobility model • Dependent (group-based mobility model)-In an ad hoc network, however, there are many situations where it is necessary to model the behavior of MNs as they move together. So the movement of MNs may depend on other’s (reference point) behavior. • Exponential correlated random mobility model • Column mobility model • Nomadic community mobility model • Pursue mobility model • Reference point group mobility model

  19. Random walk mobility model(3/8) • The random walk mobility model was first described mathematically by Einstein in 1926 in order to mimic erratic motion such as Brown Motion. • In this mobility model, a MN moves from its current location to a new location by randomly choosing a direction and speed in which to travel at a predefined step number or time slots. After choosing a new speed and direction, the new path is decided. • The new speed and direction are both chosen from [speedmin, speedmax] and [0, 2π] • The model is a memoryless mobility pattern because it retains no knowledge concerning its past locations and speed values when deciding the next speed and direction. (The defectives can be modified by the Guass-Markov model.) • If the specified time (or specified time) a MN moves in the model is short, then the movement pattern is a random roaming pattern restricted to a small portion of the simulation area.

  20. Random walk mobility model(4/8) Start point: (150, 300) Speed range: o~10 m/s-1 Direction:0~2π Time slot: 60s

  21. select n-1th Gauss r.v.: n-1th instance: n-th instance: Gauss-Markov mobility model(5/8) • The Gauss-Markov Mobility Model was designed to adapt to different levels of randomness via one tuning parameter. At fixed intervals of time, n, movement occurs by updating the speed and direction of each MN. Specifically, the value of speed and direction at the n-th instance is calculated based upon the value of speed and direction at the (n-1)-st instance and a random variable using the following equations.

  22. Gauss-Markov mobility model(6/8) Start point: (150, 300) Simulation time: 1000s α=0.75 Speed is fixed at 10 m/s-1 Mean direction is initial 90 degrees. Eliminate the sudden stops and sharp turns. The Markov process can be applied to the x and y equation directly instead of through speed and direction variables. Change direction mean

  23. Vj θj j Vi r d θi i b ODMRP on-demand multicast t Routing Protocol in Multi-hop Wireless Mobile Networks(7/8) • Adapting the Refresh Interval via Mobility Prediction Suppose 2 nodes i and j are within the transmission range r of each other. • (xi, yi) : co-ordinates of mobile host I • (xj, yj): co-ordinates of mobile host j • vi and vj: speeds of i and j respectively • oi and oj: moving directions of I and j respectively • Amount of time i and j will stay connected is predicted by: • a= vi cos oi - vj cos oj vj • b= xi – xj • c= vi sin oi - vi sin oj and • d= yi - yi

  24. t0 t0+t1 t0+t1+t2 t0+t1+t2+t3 t0+t1+t2+t3+T t1蒐集位置資訊與mobility資訊，包括速度與方向 t2 optimal algorithm computation time t3 routing decision distribution time T是此次決策使用的時間 在T快結束之前，保留的時段t1+t2+t3作下一次cluster的決策 ODMRP on-demand multicast t Routing Protocol in Multi-hop Wireless Mobile Networks-prediction(8/8) • Due to the mobility effect, it’s necessary to predict the mobility information at t0+t1+t2+t3 first to make the decision more suitable for the scenario at t0+t1+t2+t3. Then we use the predicted mean value and ODMRP formula to compute the link duration (or reliability of the consecutive path).

  25. Outline • Problem statement • Previous work • Mobility research • Cluster construction • Integer formulation for clustering • Energy-efficient multicasting and wireless advantage • My work

  26. Integer formulation for clustering(1/7) • Minimum power broadcast trees for wirelessnetworks: Integer programming formulations[INFOCOM 2003, 30 March-3 April 2003, p1001- 1010 vol.2][auhtor: Das, A.K. Marks, R.J.   El-Sharkawi, M.   Arabshahi, P.   Gray, A. Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA] • Clique and clustering: A combinatorial approach [Mathematical Programming, 62, 133-151][author: E. L. JOHNSON, A. MEHROTRA, and G. L. NEMHAUSER, 1993. Min-cut clustering ] • Load-balance clusters in wireless ad hoc networks [Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology 2000, P.25][author: alan D. Amis, Ravi Prakash] • On the optimal clustering in mobile ad hoc networks [Proceedings of IEEE Consumer Communications and Networking, Las Vegas, Nevada USA/ January 5-8, 2004 ][author: Jamal N. Al-Karaki Ahmed E. Kamal Raza Ul-Mustafa Laboratory for Advanced Networks Dept. of Electrical and Computer Engineering]

  27. Clique and clustering: A combinatorial approach- basic model for clustering(2/7) (E: the link set, we: the link weight; ye: the link decision variable for cluster) (objective to minimize the total weights of clusters) Subject to: (K: no. of clusters, zie: the belongness decision variable for node i and cluster k; V: the node set) (F: maximum cluster capacity; maximum flow constraint for the cluster k) (the flow balance constraint for the multicast tree of the cluster k) Integer constraint

  28. On the optimal clustering in mobile ad hoc networks(3/7) • A Mobile Ad hoc Network (MANET) can be represented by a set of logical clusters with clusterheads (CHs) acting like virtual base-stations, hence forming a wireless virtual backbone. The role of clusterhead is a temporary role, which changes dynamically as the topology or other factors affecting it change. The proposes includes: • Reduce protocol overhead • Minimize storage requirement • Trade-off of the network performance due to the large No. of CHs • Hop count • Communication overhead • Extra energy consumption • In this paper, the author proposed a heuristic approach VGA (virtual grid architecture) and ILP formulation for clustering.

  29. On the optimal clustering in mobile ad hoc networks-heuristic(4/7) • In VGA clustering, the network area is divided into fixed, disjoint, and regular shape zones (square). Each mobile node is a member of one of those zones and its zone membership is determined based on its location in the network area. • The clusterheads of adjacent zones can communication to each other directly. If the zone has only short rangenodes, the zone is further divided into four sub-zones.

  30. On the optimal clustering in mobile ad hoc networks- heuristic(5/7) The extension to diagonal routing, henceforth called Diagonal VGA (D-VGA), is possible but it may complicate routing since the number of potential neighbor zones doubles. In D-VGA CHs can communication with CHs of diagonal zones besides the vertical and horizontal zones.

  31. ILP notation On the optimal clustering in mobile ad hoc networks- formulation(6/7)

  32. On the optimal clustering in mobile ad hoc networks- formulation(7/7) Formulation The belonging constraint The link usage constraint The xii constraint The existence of inter-cluster routing The inter-cluster routing constraint use CH as intermediate nodes

  33. Outline • Problem statement • Previous work • Mobility research • Cluster construction • Integer formulation for clustering • Energy-efficient multicasting and wireless advantage • My work

  34. Energy-efficient multicasting and wireless advantage(1/6) • Algorithms for energy-efficient multicasting in static ad hoc network [Mobile Networks and Applications 6,251-263,2001][Author： JEFFREY E. , WIESELTHIER, GAM D. NGUYEN Information Technology Division, Naval Research Laboratory, Washington] • On reducing broadcasting redundancy in ad hoc network [IEEE transactions on mobile computing April-June 2002][Author: Wei Lou, Student Member, IEEE, and Jie Wu, Senior Member]

  35. Algorithms for energy-efficient multicasting in static ad hoc network - Wireless communication advantage (2/6) • Normalize transmission power on link (I,j) by range r and proportional factorPij = power needed to support link between nodes i and j =rα where r is the distance between nodes i and j and α is the decade factor Pi,(j,k) = max{Pij, Pik } is sufficient to reach both node j and node k, based on our assumption of omnidirectional antennas.“Wireless Multicast advantage” Cited from [Algorithms for Energy-Efficient Multicasting in Static Ad Hoc Wireless Networks] Mobile Networks and Applications 6,251-263,2001

  36. Algorithms for energy-efficient multicasting in static ad hoc network - suggested approach (3/6) • By the way, transmission power range affect connectivity and construction of spanning tree. Some additional nodes may be needed as relay to provided connectivity to all memberships of the multicast group. (relayed nodes) • Two basic approaches to construct multicast tree and using PIM (Spare mode of the protocol independent Multicasting) on the trees - Source-Based Tree (SBT) - Core-Based Tree (CBT)

  37. On reducing broadcasting redundancy in ad hoc network (DP) – energy-efficient consideration (4/6) • For reducing redundancy transmissions and prolong the life of the network, the DP algorithm utilizes 2-hops neighborhood information. Node v uses N(N(u)), N(u), and N(v) to obtain U(u, v) = N(N(v)) - N(u) - N(v) and B(u, v) = N(v) - N(u). Node v then calls the selection process to determine F(u, v) (forward node list). Cited from [On Reducing Broadcast Redundancy in Wireless Ad Hoc Network] Wei Lou, Student Member, IEEE, and Jie Wu, Senior Member, IEEE From IEEE transactions on mobile computing April-June 2002

  38. On reducing broadcasting redundancy in ad hoc network (TDP) – energy-efficient consideration (5/6) If node v can receive a packet piggybacked with N(N(u)) from node u, the 2-hop neighbor set that needs to be covered by v’s forward node list F is reduced to U = N(N(v)) – N(N(u)). Node v uses N(N(u)), N(u), and N(v) to obtain U(u, v) = N(N(v)) – N(N(u)) and B(u, v) = N(v) - N(u).

  39. On reducing broadcasting redundancy in ad hoc network (PDP) – energy-efficient consideration (6/6) Besides excluding N(u) and N(v) from N(N(v)), as addressed in the DP algorithm, more nodes can be excluded from N(N(v)). These nodes are the neighbors of each node in . Such a node set is donated as. Node v uses N(N(u)), N(u), and N(v) to obtain and U = N(N(u)) - N(u) - N(v) – P, B = N(v) – N(u).

  40. Outline • Problem statement • Previous work • Mobility research • Cluster construction • Integer formulation for clustering • Energy-efficient multicasting and wireless advantage • My work

  41. My work- problem statement • Assumption (given parameter and environment situation) • Node set and link set • All possible paths between any node pair (pre-computed) • O-D pair and desired traffic load • Capacity for each node • Mobility information of each node (location, velocity and direction) • For location-based management and resource allocation in dynamic MANETs, I want to group the nodes into cluster including the following considerations: • Determine the relationship for clusterhead and cluster member for each node pair • Determine which node would be selected as a CH • Determine the inter-cluster routing between the clusterhead and cluster members • Determine the gateway node between two clusters • Determine the link used for the cluster construction • Determine the O-D pair routing path

  42. My work-notation

  43. My work- notation

  44. My work- formulation Objective function: Maximize the minimum link T duration and node duration W Subject to: (1) The cluster member belonging constraint (2) (3) The intra-cluster routing constraint The d-hop routing constraint (4) (5) The intra-cluster routing constraint for sub-tree-construction (6)

  45. Cluster member CH Clusterhead v Constraint (5) (6): Node v 到CH間存在多條paths Constraint (3): Node v 到CH間存在多條paths My work- formulation

  46. t0 t0+t1 t0+t1+t2 t0+t1+t2+t3 T t0+t1+t2+t3+T My work- formulation (7) The cluster gateway node constraint (8) The cluster gateway node belonging constraint (9) (10) The cluster connectivity constraint (11) The cluster duration constraint (12)

  47. Cluster n and CH n Cluster m and CH m Gateway node v, u between cluster m and n My work- formulation Constraint (7) (8):The cluster gateway node constraint 若u、v兩個nodes相鄰(存在有hop count為一的路徑)，且u、v兩個nodes分屬不同的cluster m和n。則u、v為兩cluster的gateway node。

  48. My work- formulation The O-D pair routing constraint (13) (14) (15) The inter-cluster routing constraint (16) The node capacity constraint (17) (18)

  49. My work- formulation (19) (20) (21) The integer constraint x 6 (22) (23) (24)

  50. End • Thanks for your attention • Discussion

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