checkpointing is then combined with a dynamic voltage scaling scheme to achieve power reduction. The resulting energy-aware adaptive checkpointing scheme uses a dynamic voltage scaling criterion that is based not only on the slack in task execution but also on the occurrences of faults during task execution

of checkpoints, which can minimize the average execution time of tasks. Further, the adaptive checkpointing is combined with the DVS (dy-namic voltage scaling) scheme to achieve energy reduc-tion. Simulation results show that, compared with the previous methods, the proposed approach significantly increases

system can guide such adaptation to yield a batterylife of desired duration. By monitoring energy supply and demand, it is able to select the correct tradeoff between energy conservation and application quality. Our evaluation shows that this approach can meet goals that extend battery life by as much

into groups of communicating nodes and the entire sensor network. By following an energy-aware design methodology based on techniques such as in this article, designers can enhance network lifetime by orders of magnitude.

In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation) , that eciently disseminates information among sensors in an energy-constrained wireless sensor network. Nodes running a SPIN communication protocol name their data using high

.11 in several ways: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses a few novel techniques to reduce energy consumption and support self-configuration. It enables low-duty-cycle operation in a multihop network. Nodes form virtual

for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network (e.g., data

Wireless Sensor Networks (WSNs) consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. The focus

In this paper we present a case for using new power-aware metrics for determining routes in wireless ad hoc networks. We present five different metrics based on battery power consumption at nodes. We show that using these metrics in a shortest-cost routing algorithm reduces the cost

We introduce a geographical adaptive fidelity (GAF) algorithm that reduces energy consumption in ad hoc wireless networks. GAF conserves energy by identifying nodes that are equivalent from a routing perspective and then turning off unnecessary nodes, keeping a constant level of routing fidelity