Nikos Dimokas1 Dimitrios Katsaros2 (presentation) Detecting Energy-Efficient ‘Central’ Nodes for Cooperative Caching in Wireless Sensor Networks Nikos Dimokas1 Dimitrios Katsaros2 (presentation) 1Aristotle University of Thessaloniki, Greece 2University of Thessaly, Greece IEEE AINA, Barcelona (Spain), 25-28/March/2013

In-network processing in a camera sensor network Query In-network processing in a camera sensor network Cooperation to get cached data Response to the sink How many foxes inside the box on 2013/03/20 @ 06:30?

Presentation outline Earlier work and background knowledge Energy paths Energy Betweenness centrality Cooperative caching with EBCCoCa Performance evaluation Conclusions

Cooperative caching: Earlier work Earlier work & background Cooperative caching: Earlier work

The concept of ‘node betweenness’ Earlier work & background The concept of ‘node betweenness’ Betweenness Centrality (BC): The SPBC index of a node is equal to the ratio of the number of shortest paths between pairs of nodes passing by this node to the total number of shortest paths between this pair of nodes 1 9 7 2 6 5 3 4 8 paths between j and k passing through v betweenness centrality of node v all paths between j and k

The concept of ‘node betweenness’ Earlier work & background The concept of ‘node betweenness’ Betweenness Centrality (BC): The SPBC index of a node is equal to the ratio of the number of shortest paths between pairs of nodes passing by this node to the total number of shortest paths between this pair of nodes 1 (0) 9 (0) 7 (13) 2 (0) 6 (7) 5 (0) 3 (10) 4 (8) 8 (0) paths between j and k passing through v betweenness centrality of node v all paths between j and k

Tunable balance between Shortest & Energy-efficient paths Energy paths Tunable balance between Shortest & Energy-efficient paths shortest energy path the multi-hop path that connects two nodes with the minimum energy dissipation among the intermediate nodes sepuw the fraction of the summation of edges’ weights (that correspond to the path) to the number of edges comprising the path Initially, each node represents its remaining energy Er as a percentage of the initial energy Ei. For node u: Eu=Er/Ei To each edge e = (u,v), we assign a weight wuv = (Eu+Ev)/2

Energy path values for edges: Example Energy paths Energy path values for edges: Example Initially, each node has 2Joules energy Paths from B→E 1.4 1.1 0.65 0.625 0.475 0.55 0.45 0.725 0.675 0.5 D C B H E F G A B→C→D→E (0.65+0.625+0.475)/3= 0.583 1 0.8 B→A→E (0.55+0.45)/2= 0.5 B→H→G→F→E (0.675+0.725+0.65+0.5)/4= 0.6375 sepBE= 0.6375

Energy Betweenness Centrality (EBC) Energy consideration Latency consideration when α = 0.0  

The datum discovery protocol (1/2) Cooperative caching with EBCCoCa The datum discovery protocol (1/2) A sensor issues a request for an item Searches its local cache and if it is found (local cache hit) then the K most recent access timestamps are updated Otherwise (local cache miss), the request is broadcasted and received by the Community Caching Nodes – CCNs (selected based on EBC) CCNs check the 2-hop neighbors of the requesting node whether they cache the datum (proximity hit) If none of them responds (proximity cache miss), then the request is directed to the ultimate data source (e.g., a fictitious Data Center)

The datum discovery protocol (2/2) Cooperative caching with EBCCoCa The datum discovery protocol (2/2) When a CCN receives a request, searches its cache If it deduces that the request can be satisfied by a neighboring node (remote cache hit), forwards the request to the neighboring node If the request can not be satisfied by this CCN, then it forwards it recursively If none of the nodes (CCNs and ordinary nodes) can help, then requested datum is served by the Data Center (global hit)

Cost-based cache replacement Cooperative caching with EBCCoCa Cost-based cache replacement Each sensor first purges the data that it has cached on behalf of some other node Calculates the following function for each cached datum i Informs the CCNs about the candidate victim CCNs determine the new hosting node based on residual energy

Evaluation setting (1/2) Performance evaluation Evaluation setting (1/2) EBCCoCa evaluated w.r.t.: impact of α competitor: NICoCa (α = 0.0) [appeared@ACM MONET’08] Parameter Default value Range #items (N) 1000 fixed # requests per node 200 Smin (KB) 1 Smax (KB) 10 #nodes (n) 500 100-1000 bandwidth (Mbps) 2 waiting interval (tw) 10 sec cache size (KB) 800 200 to 800 Zipfian skewness (θ) 0.8 0.0 to 1.0

Evaluation setting (2/2) Performance evaluation Evaluation setting (2/2) Measured quantities network longevity (first node dies) average latency for getting the requested data number of remote hits Large number of remote hits  effectiveness of cooperation  small latency

Impact of network size (θ = 0.8) on longevity in a sparse WSN (d = 4) Performance evaluation Impact of network size (θ = 0.8) on longevity in a sparse WSN (d = 4)

Impact of network size (θ = 0.8) on longevity in a dense WSN (d = 10) Performance evaluation Impact of network size (θ = 0.8) on longevity in a dense WSN (d = 10) 20% up in longevity: In a denser network, more node-disjoint paths are available

Impact of α (θ = 0.8) on latency in a sparse WSN (d = 4) Performance evaluation Impact of α (θ = 0.8) on latency in a sparse WSN (d = 4) α

Impact of α (θ = 0.8) on latency in a dense WSN (d = 10) Performance evaluation Impact of α (θ = 0.8) on latency in a dense WSN (d = 10) α

Impact of α (θ = 0.8) on cooperation in sparse WSN (d = 4) Performance evaluation Impact of α (θ = 0.8) on cooperation in sparse WSN (d = 4) α

Impact of α (θ = 0.8) on cooperation in dense WSN (d = 10) Performance evaluation Impact of α (θ = 0.8) on cooperation in dense WSN (d = 10) α

Summary Performance issues for WSNs Conclusions Summary Performance issues for WSNs Jointly optimize in a localized manner the nodes’ energy & latency for cooperative caching: EBCCoCa EBCCoCa: increases the remote hits (due to the effective sensor cooperation) identifies energy-efficient paths tunable for energy vs. latency considerations

References (a sample of significant/representative ones) P. Nuggehalli, V. Srinivasan, C-F. Chiasserini. Energy-efficient caching strategies in ad hoc wireless networks. Proc. ACM MOBIHOC, 2003. L. Yin and G. Cao. Supporting cooperative caching in ad hoc networks. IEEE Transactions on Mobile Computing, 5(1):77-89, 2006. N. Dimokas, D. Katsaros, Y. Manolopoulos. Cooperative caching in wireless multimedia sensor networks. ACM Mobile Networks and Applications, 13(3-4), 337-356, 2008. Y. Du, S.K.S. Gupta, G. Varsamopoulos. Improving on-demand data access efficiency in MANETs with cooperative caching. Ad Hoc Networks, 7(3), pp. 579–598, 2008. M.K. Denko, J. Tian, T.K. R. Nkwe, M.S. Obaidat. Cluster-based cross-layer design for cooperative caching in mobile ad hoc networks. IEEE Systems Journal, 3(4), 499-508, 2009. E. Chan, W. Li, D. Chen. Energy saving strategies for cooperative cache replacement in mobile ad hoc networks. Pervasive and Mobile Computing, 5(1), 77-92, 2009. N. Chauhan, L.K. Awasthi, N. Chand, R.C. Joshi, M. Misra. Energy efficient cooperative caching in mobile ad hoc networks. International Journal of Applied Engineering Research, 1(3), 360-371, 2010. N. Dimokas, D. Katsaros, Y. Manolopoulos. High performance, low complexity cooperative caching for wireless sensor networks. ACM Wireless Networks, 17(3), 717-737, 2011. N. Chauhan, L.K. Awasthi, N. Chand. Cluster-based efficient caching technique for wireless sensor networks. Proc. IEEE ICLCT, 2012.

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