This paper presents Pirrus, a replica management system that addresses the problem of providing data availability on a wireless sensor network. Pirrus uses probabilistic failure models (e.g., derived from environmental conditions and esti- mation of available energy) to adaptively create and maintain a number of replicas of the data. Replica management is formulated as an energy optimization problem, then solved with a greedy heuristic that only uses information gathered from neighbors. Intuitively, Pirrus trades off the energy saved by limiting the number of replicas when the network health is good to extend the lifetime when more replicas are needed. Our simulation results show how the solution provided by Pirrus achieves good performance with a sustainable computational cost. Compared to the performance of a fixed number of replicas, Pirrus extends the network lifetime by more than 20%. fault or battery depletion, the data it stores is lost. Therefore, replicating data on multiple nodes represents a method for reducing the possibility of data loss. Due to the limited resources in sensor networks, the main challenge is defining the number and placement of the replicas to support high data availability while maintaining long network lifetime. Data replication has been proposed to prevent such data loss in distributed environments. Traditional replication approaches use a fixed number of replicas defined a-priori during network deployment (1). Given the dynamic failure potential of the nodes in the network, these static solutions are either too expensive or cannot provide enough availability during the network lifetime. To cope with the variability in the network, replica management should be adaptive and adjust the number and location of replicas to provide the same data availability. The contribution of our research is threefold. First, we formalize the problem of providing energy-efficient replica placement for data availability as an energy optimization prob- lem. Given that the optimal solution requires global knowledge of network state, we next define a heuristic approach that only requires local information. Finally, we adapt the heuristic approach to design a novel distributed protocol, called Pirrus, which adopts a greedy approach and provides near-optimal results under varying conditions. The key idea in Pirrus is that each node only uses lo- cal information about their n-hop neighbors to solve the problem of space availability. This local approach scales to large networks without suffering from excessive overhead or computational complexity. Since the environment has a strong influence on node reliability, Pirrus is designed to be flexible and allows users to define appropriate probabilistic failure models. In comparison to static approaches that do not consider the reliability of the nodes in the network, Pirrus adapts to changing network conditions. When data availability is a priority, results show that Pirrus is able to extend network lifetime compared to other approaches. The rest of the paper presents the replica placement problem and describes our approach to solve it. Section II presents an overview of the problem of adaptive data replication. Sec- tion III formalizes the replica placement problem. Section IV describes the Pirrus protocol and its replica placement strategy. Section V presents an evaluation of Pirrus in comparison to other approaches.
['Riccardo Crepaldi', 'Mirko Montanari', 'Indranil Gupta', 'Robin Kravets']
Using Failure Models for Controlling Data Availability in Wireless Sensor Networks