Mahesh Arumugam

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Michigan State University, East Lansing, MI 48824 Abstract Reliable dissemination of bulk data is one of the important problems in sensor networks. For example, programming or upgrading the software in sensors at run-time requires reliable dissemination of a new program across the network. In this paper, we present Infuse, a time division multiple access(More)
Dependable properties such as self-stabilization are crucial requirements in sensor networks. One way to achieve these properties is to utilize the vast literature on distributed systems where such self-stabilizing algorithms have been designed. Since these existing algorithms are designed in read/write model (or variations thereof), they cannot be directly(More)
An algorithm for time division multiple access (TDMA) is found to be applicable in converting existing distributed algorithms into a model that is consistent with sensor networks. Such a TDMA service needs to be self-stabilizing so that in the event of corruption of assigned slots and clock drift, it recovers to states from where TDMA slots are consistent.(More)
The designer of a sensor network protocol needs to address several low-level details such as message collisions, message losses, and resource limitations. Also, the designer needs to solve several high-level problems such as routing, leader election, and diffusing computation that are already considered in distributed systems and traditional networking.(More)
ProSe hides low-level details from the designer. ProSe also preserves fault-tolerance properties of original program during transformation. Based on our results from [11], [17] on prototyping target tracking and power management protocols with ProSe, we expect ProSe to enable domain experts design sensor network protocols rather than experts in sensor(More)
In this paper, we focus on the problem of approximate causal delivery. This problem identifies the tradeoff between causal delivery and timely delivery of messages. Causal delivery requires that delivery of a message, say m, be delayed until all messages on whom m is causally dependent are delivered. By contrast, timely delivery requires that messages be(More)