load balanced link reversal routing in mobile wireless ad hoc networks
DESCRIPTION
Load Balanced Link Reversal Routing in Mobile Wireless Ad Hoc Networks. Costas Busch CSCI Department RPI. Nabhendra Bisnik, Alhussein Abouzeid ECSE Department RPI. Mobile Wireless Networks. Wireless nodes are mostly battery driven ) limited transmission range Nodes act as relays - PowerPoint PPT PresentationTRANSCRIPT
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Load Balanced Link Reversal Routing in Mobile Wireless Ad
Hoc Networks
Load Balanced Link Reversal Routing in Mobile Wireless Ad
Hoc NetworksNabhendra Bisnik, Alhussein
AbouzeidECSE Department
RPI
Costas BuschCSCI
DepartmentRPI
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Mobile Wireless NetworksMobile 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)
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ContributionsContributions
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
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Talk OutlineTalk Outline
Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
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Talk OutlineTalk Outline
Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
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Link Reversal RoutingLink 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
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Route Creation PhaseRoute Creation Phase
DestinationHeight = 0
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Directed Acyclic Graph(DAG)
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) = [h1(a), h0(a) ] where h1(a) = height assigned by LRR and h0(a) = node id of a Lexicographical ordering used
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Route Maintenance PhaseRoute Maintenance Phase
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Full Link Reversal Algorithm
Brings network from a bad stateto a good state Runs in (n2) time Leads to increase in height of at least one node
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Talk OutlineTalk Outline
Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
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Causes of Load UnbalanceCauses 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
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Load Unbalance - ExampleLoad Unbalance - Example
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Although alternate path is now available, most of the traffic is still routed through the node with height 5
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Unbalanced Network StateUnbalanced 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) > 2 and a ! b exists in the DAG)
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High HeightGradient
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Talk OutlineTalk Outline
Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
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Load Balancing ProblemLoad 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, xS
(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)
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Load Balancing ProblemLoad Balancing Problem
From optimization point of view, the load balance problem is to find and s.t.
This problem is NP-hard, distributed
solution is even more difficult
Or,
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Talk OutlineTalk Outline
Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
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Heuristic MechanismsHeuristic 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
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Selfish Node Based Mechanism
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 hmax – hmin > 2 then
Sets height to minimum height that ensures path to the destination
Fix link directions Update neighors
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Selfish Node Based Mechanism
Selfish Node Based Mechanism
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Selfish Node Based Mechanism
Selfish Node Based Mechanism
However every instances of load unbalance does not involve selfish nodes
Example ) Solution – reduce height
whenever it is possible inorder to balance DAG
This observation leads to PDH
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Proactive Decrease in Height
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
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Proactive Decrease in Height
Proactive Decrease in Height
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Reactive Increase in HeightReactive 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 hmax + 1 Fix link directions Update neighbors
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Reactive Increase in HeightReactive Increase in Height
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Forwarding StrategiesForwarding 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
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Talk OutlineTalk Outline
Link Reversal Routing Causes of load unbalance Load balancing problem Heuristic mechanisms Simulations
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Simulation SettingSimulation Setting
N mobile nodes, initially deployed randomly over 1000m £ 1000m area
Communication radius is m Random waypoint mobility model used
with vmin = 2m/s, vmax = 5m/s, pause time = 5s
Each node generates traffic at rate 1Kbps, destined to a sink node
Sink node located at (500m, 500m) Models mobile wireless sensor network,
multi-hop wireless mesh networks
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Performance MetricsPerformance Metrics
Balance factor and squared sum for both multi-path and shortest path forwarding
Network lifetime Routing updates
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Balance FactorBalance Factor
PDH has highest balance factor As number of nodes increases, path length increases leading to lower balance factorMulti-path routing has larger balance factor
Multi-path routing Shortest path routing
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Squared SumSquared Sum
Multi-path routing Shortest path routing
Again PDH has smaller squared sum Multi-path routing leads to longer routes, hence larger squared sum
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Network LifetimeNetwork Lifetime
PDH leads to highest network lifetime Lifetime decreases with increase in number of nodes
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Height Update RateHeight 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 higheroverhead
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Conclusion and Future WorkConclusion 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-2 implementation of the proposed
schemes Approximate algorithms based on
optimization framework
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Thank You!Thank You!
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