A distributed sensor network (DSN) consists of sensor nodes with limited energy source, sensor devices, short-range radio and on-board processing capability. Sensing capability of the attached sensing devices and their small size, make these sensor nodes highly suitable for habitat monitoring. Every physical event leaves some fingerprints in the environment in terms of the event's effect; e.g., fire increases temperature, chemical spilling increases contamination, nuclear leakage increases radiation. Moreover, most of the physical phenomena follow diffusion property with distance, i.e., where d is the distance from the point having maximum effect of the event, f (d) is magnitude of the event's effect and α is the diffusion parameter depending on the type of effect; e.g., for light α = 2, heat α 1. As an example, if some location's temperature is 100 o C then, nearby locations temperature should be correlated with that based on the distance. Thus the property of physical phenomena implicity creates a distributed information repository about the event's effect. So, routing protocols for DSN can exploit this natural, information gradient as an important attribute to forward the query efficiently towards the source. Characteristics of the sensor nodes, i.e., limited battery life, energy expensive wireless communication, high probability of failure or malfunction and unstructured nature of the DSN, make routing in the DSN a challenging problem. Traditional routing protocols of the DSN are based mostly on flooding (Directed Diffusion[1]) or random-walk (ACQUIRE[2] ). These approaches, however, do not utilize the domainspecific knowledge, i.e., the event's fingerprint gradient about the monitored phenomenon. Previous datacentric routing protocols that are based on information gradient [3] , use a proactive phase to prepare distributed or cluster based gradient information repository towards a target or an event. To adapt to dynamic behavior of DSN, periodic update of information repository is required. To route a query from sink * This research is supported by Pratt&Whitney UTC Institute for Collaborative Engineering (PWICE), Intel and NSF CAREER awards. to source, most of these protocols use greedy routing algorithms based on information gradient. For preparing gradient information repository and routing query, protocols do not take advantage of using well established law of physical events. Moreover, the query proceeds towards the source through a single path, which usually get trapped at the local maxima or minima, or reach a dead-end due to imperfect sensor device and environmental noise. On the other hand, creating unlimited multiple paths resembles flooding. In this paper, we propose a scheme to effectively exploit the fingerprint gradient of the event's effect to avoid the proactive phase of preparing distributed gradient information repository and a novel energy efficient, fully distributed and reactive routing protocol based on that information gradient. Our protocol effectively exploits the laws of physical events for routing decision. Also it overcomes the limitations of usual information-driven routing protocols due to local maxima or minima using simulated annealing concepts in a distributed manner and establishes an effective balance between single path and multiple path exploration to discover routes.
In the context of sensor networks, the study in REF exploits the natural information gradient exhibited by physical phenomena to efficiently route queries toward the event source.
Gradient-based routing in sensor networks
MOCO
Computer Science