Issue No. 08 - Aug. (2012 vol. 23)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.296
M. Elena Renda , IIT—National Research Council, Pisa
Giovanni Resta , IIT—National Research Council, Pisa
Paolo Santi , IIT—National Research Council, Pisa
In this paper, we address the problem of balancing the network traffic load when the data generated in a wireless sensor network is stored on the sensor node themselves, and accessed through querying a geographic hash table. Existing approaches allow balancing network load by changing the georouting protocol used to forward queries in the geographic hash table. However, this comes at the expense of considerably complicating the routing process, which no longer occurs along (near) straight-line trajectories, but requires computing complex geometric transformations. In this paper, we demonstrate that it is possible to balance network traffic load in a geographic hash table without changing the underlying georouting protocol. Instead of changing the (near) straight-line georouting protocol used to send a query from the node issuing the query (the source) to the node managing the queried key (the destination), we propose to “reverse engineer” the hash function used to store data in the network, implementing a sort of “load-aware” assignment of key ranges to wireless sensor nodes. This innovative methodology is instantiated into two specific approaches: an analytical one, in which the destination density function yielding quasiperfect load balancing is analytically characterized under uniformity assumptions for what concerns location of nodes and query sources; and an iterative, heuristic approach that can be used whenever these uniformity assumptions are not fulfilled. In order to prove practicality of our load balancing methodology, we have performed extensive simulations resembling realistic wireless sensor network deployments showing the effectiveness of the two proposed approaches in considerably improving load balancing and extending network lifetime. Simulation results also show that our proposed technique achieves better load balancing than an existing approach based on modifying georouting.
Geographic hash tables, load balancing, wireless sensor networks, in-network data storage, network lifetime.
M. E. Renda, P. Santi and G. Resta, "Load Balancing Hashing in Geographic Hash Tables," in IEEE Transactions on Parallel & Distributed Systems, vol. 23, no. , pp. 1508-1519, 2011.