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IEEE DCOSS’12

IEEE DCOSS’12. Mitigate Funnel Effect in Sensor Networks with Multi-Interface Relay Nodes. Jorge Mena University of California, Los Angeles Mario Gerla University of California, Los Angeles Vana Kalogeraky Athens University of Economics and Business. 17 de Mayo de 2012.

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IEEE DCOSS’12

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  1. IEEE DCOSS’12 Mitigate Funnel Effect in Sensor Networks with Multi-Interface Relay Nodes Jorge Mena University of California, Los Angeles Mario Gerla University of California, Los Angeles VanaKalogeraky Athens University of Economics and Business 17 de Mayo de 2012

  2. Network Research Lab (NRL) • Vehicular Network (VaNet) • Traffic congestion modeling and car sensor network projects • WiMax/WiFitestbed that spans the UCLA campus. • Network Coding • Cognitive Networks (CogNets) • Application, protocol stack and Physical sensing spectrum allocation research • Mobile Health Networks • PAN with UVA/UVB sensors research • Radioactive particles sensor research (coming soon)

  3. Sensors Networks • Transceivers adapted with a sensor devices (temp, motion, particles, etc.) • Disposable, low-cost, low-performance • Sink node • Powerful, reusable, resourceful • Final destination of all data flows • Sensors establish ad-hoc networks with the goals to sense their surrounding environment and generate update data flows to the sink. Mica2 sensor

  4. The problem we address • Funnel effect problem • Sensor networks with high activity may generate large data flows. • Flows from remote areas converge at the region that surrounds the sink • Consuming resources: bandwidth, power • Duty cycles conserves energy and saves bandwidth but may disconnect the network • Decreases the number of available paths to sink • Available paths consume the little bandwidth • Sensors compete for bandwidth and scarse • Intense usage of spectrum resources and energy at the areas that surround the sink due to remote flows.

  5. Preliminary view for a solution If the problem is with resources… … add more… … or even more.

  6. Relay Node Network • Relay nodes • Mobile devices adapted with multiple radio interfaces and larger power and computational resources • They establish overlay networks using orthogonal (non-interfering) channels on top of the sensor network. • More resources are added since there is no competition for the bandwidth • Using a second interface, a relay may pick up and drop off packets from the sensor network • Solution approach: • Use an network of relay nodes that uses orthogonal channels to provide additional resources to the sensor network that experiences the funnel effect.

  7. Problem Statement • Now that we have an idea of what to do, the main question is: How do we deploy such a network with the minimum number of relay nodes that mitigate the funnel effect? • Our contribution • A placement algorithm • Minimum number of relay nodes

  8. Network Model • A standard 2-D wireless network • n nodes • A unidirectional graph G(V,E) • V is the set of vertices (nodes) • E is the set of edges (links) • A subset of available channels Cu for each node u from the total set C. • A transmission range r • Eucledian distance d(u,v) between two nodes u and v • Edge e = (u,v) belongs to E if • d(u,v) < r (the two nodes hear each other) • Intersection of Cu and Cv is not empty (there is at least one common channel)

  9. Assumptions • A node u is able to tune its interfaces to any of its channels c in Cu • A sensor has only one interface that is tuned to a common channel c • A relay node has at least two interfaces that may be tuned to any channel in C • Static assignment or some channel assignment algorithm • Relay nodes may be potentially connected to several networks at the same time. • SDR, AODV routing for within the intra-net; static routes for inter-nets. • A decision is made at a relay node to accept traffic or not (policy based through route announcement).

  10. Funnel Effect Mitigation – Congested Region • Congested Region • A group of nodes characterized by their proximity that experience a high demand of their resources. • A node is considered congested if its local statistics surpass some threshold • ETD, packet drops, jitter, etc. • A message exchange protocol with high priority on control packets determine this region and forms a cluster with a well-defined boundary (its Convex Hull)

  11. Funnel Effect Mitigation – Basic Intuition • Two remote sensor nodes, S1 and S2 may be connected by a relay node R provided that it is placed within the intersection of the sensors’ ranges: r < d(S1,S2) ≤ 2r

  12. FEM – Relay Placement • Given a congested region and our basic intuition, cover the region with relays • In a circular-manner, cover the convex hull until all the edge nodes are connected to at least one relay node • Repeat with the inner ring of relay nodes • Stop when the inner-most ring is connected to the sink.

  13. Placement Condition • To approach the minimal number of relay nodes, we use the placement condition: The geographical location of a new relay node is that which covers the largest amount number of elements and it is closest to the sink

  14. Placement Condition • Node proximity: The minimum allowed proximity distance for two nodes to be covered by one relay is r√(3) • This guarantees that a relay node is placed at a location at least r/2 units closer to the sink from the midpoint of the segment of two nodes being covered • extent is the parameter that controls up to what node proximity the new relay will cover.

  15. Node Extent d(S1,S2) ≤ r × extent < 2r

  16. Placement Theory • Theorem 1 If the point c (slide 18) lies within the placement area, then it is the only geographical location that satisfies the placement condition. • Corollary 1 If the point c lies outside the placement area, then the closest point a or b to c has the best placement.

  17. Three Scenarios (First)

  18. Three Scenarios (Second)

  19. Three Scenarios (Third)

  20. The Placement Algorithm • Input: Congested region C, sink, extent • Output: List R of relay node placements • R = 0 • if all elements in C are covered, return R • C’ = Convex Hull(C) • Sort C’ so we can visit each element in clock-wise order (make a ring) • for each element e in C’ not covered: • if e reaches the sink, mark it as covered and continue the loop • find the simple best placement p for e and mark it as covered • for each e’ in C’ after e that is not covered: • if d(e,e’) > r x extent, break this loop • find the best placement q for the triangle (e,e’,sink) and mark e’ as covered • R = R U Closest(sink,{p,q}) • return Algorithm1(R, extent, sink)

  21. The Placement Algorithm

  22. Algorithm Analysis • The complexity time to calculate the Convex Hull of a set C of size m is O(mlog(h)), for h being the number of elements in the hull. • Sorting C’ takes O(hlog(h)) • The nested loops visit every single element in the hull (h) exactly one time, so it’s linear • Since m>h, the dominating factor is the repeated calculations of the convex hull • Due to the placement condition, for every recursive call, the algorithm advances at least r/2 units closer into the sink. • rC’ is the radius of first Convex Hull. There are rC’/r/2 = 2rC’/r number of recursive calls (constant) • So the overall complexity is dominated by O(mlog(h))

  23. Experiment Settings • Simulation QualNet 5.0 • 1000m by 1200m flat terrain with Rayleigh fading model (forrest, debris) • 40 sensors, 1 sink, 7 feeding sensors • WiFi 2Mbps Tx rate, 200m Tx range, 32-Byte packet size at 4/sec (local traffic) • Foreign sensors simulate the rest of the network by generating packets of size 1KB at a rate of 2/sec.

  24. Metrics Observed • Throughput observed per node • E2E Delay observed per node • Jitter of the data flow • inter-packet arrival gap of two consecutive packets sent from the same source.

  25. Naïve Placement Strategy

  26. Results (Number of Relays) Placement Constraint: Our strategy tries to maximize the coverage of nodes by choosing the location that covers the most elements in the convex hull AND is the closest to the sink.

  27. Results (Avg. Throughput) Funnel Effect. Without relays, we observe little throughput, mostly from the nodes inside the Congested Region. As a consequence, the foreign nodes starve.

  28. Results (Avg. E2E Delay) With relays the network stabilizes.

  29. Results (Jitter Observed) The relay network improves the availability of data due to the addition of new path resources.

  30. Conclusions • Placement condition guarantees minimum number of relay nodes used • 43% less relays used • O(mlog(h)) algorithm • Improves observed throughput and delivery ratio • It stabilized the transmission delay • Less oscillations of data flows • Decreases the jitter, making packets more readily available

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