Load Balanced Link Reversal Routing in Mobile Wireless Ad Hoc Networks Nabhendra Bisnik, Alhussein Abouzeid ECSE Department RPI Costas Busch CSCI Department RPI
Mobile Wireless Networks Wireless nodes are mostly battery driven ) limited transmission range Nodes act as relays Often involves many-to-one communication Multihop wireless mesh networks Mobile sensor networks Link reversal routing (LRR) is a good choice Loop free routes Low overhead However LRR may lead to unbalanced distribution of load (traffic forwarded)
Contributions Identify the causes of load unbalance in LRR Propose three heuristic mechanisms that attack different causes of load unbalance Evaluate the performance of the heuristics using simulations
Talk Outline Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
Talk Outline Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
Link Reversal Routing Properties Distributed Loop free at every instant Low overhead Offers both proactive and reactive modes Multiple routes to destination Two phases Route creation phase Route maintenance phase
Route Creation Phase Destination Height = Directed Acyclic Graph (DAG) QRY UPD Route creation phase assigns height to each node and transforms connected network into a DAG a! b exists in the DAG only iff h(a) > h(b) Thus DAG is loop free In general h(a) = [h (a), h (a) ] where h (a) = height assigned by LRR and h (a) = node id of a Lexicographical ordering used
Route Maintenance Phase 7 7 7 8 7 8 Full Link Reversal Algorithm Brings network from a bad state to a good state Runs in (n ) time Leads to increase in height of at least one node
Talk Outline Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
Causes of Load Unbalance Traffic flows from higher height to lower height Each time a node looses route to the destination, its height increases The nodes with stable routes to destination tend to have lower height Thus stable nodes relay large amount of traffic leading to Battery exhaustion Congestion
Load Unbalance - Example 8 7 8 7 7 8 7 8 Although alternate path is now available, most of the traffic is still routed through the node with height
Unbalanced Network State If there exist routes to the destination in the undirected network graph whose use may lead to a more uniform spread of load, but the routes are absent in DAG Characteristics of unbalanced network state Selfish nodes (nodes with no incoming links) High height gradients (h(a) h(b) > and a! b exists in the DAG) Selfish Node High Height Gradient C B K A J I H L D G E F Isolated Routing Components
Talk Outline Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
Load Balancing Problem Two Components of the problem Maintaining a good DAG ( ) Use good forwarding strategy over the DAG (S ) Forwarding Strategy maps a link l of the DAG to traffic flowing over it, x S (l) Total traffic forwarded by a node where E (i) is the set of outgoing links of node i Load balance metrics Balance Factor (BF) Squared Sum (SS)
Load Balancing Problem From optimization point of view, the load balance problem is to find and s.t. Or, This problem is NP-hard, distributed solution is even more difficult
Talk Outline Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
Heuristic Mechanisms Three heuristic mechanisms Selfish Node Based Mechanism (SNBM) Proactive Decrease in Height (PDH) Reactive Increase in Height (RIH) Height manipulation Decrease height ) attract traffic Increase height ) repel traffic
Selfish Node Based Mechanism Aims to balance the size of isolated routing components Periodically each node checks if it is selfish If node selfish then If h max h min > then Sets height to minimum height that ensures path to the destination Fix link directions Update neighors
Selfish Node Based Mechanism C B A D I E F J H K L 7 8 G C B A D I E F J H K L G C B A D I E F J H K L 7 G C B A D I E F J H K L G C B A D I E F J H K L G
Selfish Node Based Mechanism However every instances of load unbalance does not involve selfish nodes M 9 8 Example ) L H Solution reduce height whenever it is possible in order to balance DAG This observation leads to PDH 7 C B A K J I D G F E
Proactive Decrease in Height Each node periodically compares its height with neighbors If it is possible to decrease height without becoming a sink, then Set height to minimum possible height that allows route to destination Fix link directions Update neighbors
Proactive Decrease in Height C B A D I E F J H K L 8 G M 9 7 C B A D I E F J H K L 8 G M 9 7 C B A D I E F J H K L 8 G M 9 C B A D I E F J H K L G M
Reactive Increase in Height Both SNBM and PDH are proactive in nature RIH acts only when needed Each node records the amount of traffic forwarded during an update window If load served during an update window exceeds threshold then Set height equal to h max + Fix link directions Update neighbors
Reactive Increase in Height A B C D G F E A B C D G F E A B C D G F E A B C D G F E 7 A B C D G F E 8 7
Forwarding Strategies Load distribution is also affected by the forwarding strategies Two forwarding strategies considered Multi-path routing Distribute load equally among all downstream links Requires maintenance of forwarding records Shortest path routing Forward packets to downstream neighbor that lies on the shortest path available in the DAG Requires no state information
Talk Outline Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
Simulation Setting N mobile nodes, initially deployed randomly over m m area Communication radius is m Random waypoint mobility model used with v min = m/s, v max = m/s, pause time = s Each node generates traffic at rate Kbps, destined to a sink node Sink node located at (m, m) Models mobile wireless sensor network, multi-hop wireless mesh networks
Performance Metrics Balance factor and squared sum for both multi-path and shortest path forwarding Network lifetime Routing updates
Balance Factor Multi-path routing Shortest path routing PDH has highest balance factor As number of nodes increases, path length increases leading to lower balance factor Multi-path routing has larger balance factor
Squared Sum Multi-path routing Shortest path routing Again PDH has smaller squared sum Multi-path routing leads to longer routes, hence larger squared sum
Network Lifetime PDH leads to highest network lifetime Lifetime decreases with increase in number of nodes
Height Update Rate An update message is produced each time height of a node is updated Thus routing overhead is proportional to the height update rate RIH may cause a chain reaction of height updates, thus has much higher overhead
Conclusion and Future Work All the proposed schemes achieve better load balance than basic LRR PDH is the best, since it is most aggressive Future Work NS- implementation of the proposed schemes Approximate algorithms based on optimization framework
Thank You!