IEEE Communications Letters
Handling dynamics in diffusive aggregation schemes: An evaporative approach
Future Generation Computer Systems
Arranging cluster sizes and transmission ranges for wireless sensor networks
Information Sciences: an International Journal
Self-organizing virtual macro sensors
ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms
MAX–MIN aggregation in wireless sensor networks: mechanism and modeling
Wireless Communications & Mobile Computing
Geographic convergecast using mobile sink in wireless sensor networks
Computer Communications
On the optimal randomized clustering in distributed sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Recently wireless sensor networks featuring direct sink access have been studied as an efficient architecture to gather and process data for numerous applications. We focus on the joint effect of clustering and data correlation on the performance of such networks. We propose a novel Cluster-based Data Collection scheme for sensor networks with Direct Sink Access (CDC-DSA), and provide an analytical framework to evaluate its performance in terms of energy consumption, latency, and robustness. In our scheme, CHs use a low-overhead and simple medium access control (MAC) conceptually similar to ALOHA to contend for the reachback channel to the data sink. Since in our model data is collected periodically, the packet arrival is not modeled by a continuous random process and, therefore, our framework is based on transient analysis rather than a steady state analysis. Using random geometry tools, we study how the optimal average cluster size and energy savings vary in a response to various data correlation levels under the proposed MAC. Extensive simulations for various protocol parameters show that our analysis is fairly accurate for a wide range of parameters. Our results suggest that despite the tradeoff between energy consumption and latency, both of which can be substantially reduced by proper clustering design.