In environments where node density is massive, placement is heterogeneous and lot of sensory traffic with redundancy is produced; waste of resources such as bandwidth and energy occurs. This waste of resources minimize the network life time. Numerous routing schemes have been proposed to address such problems. They all tend to focus on similar direction, i.e. to find minimum energy path to increase the life time of the network. In this paper, we argue that it is not always wise to use the minimum energy path. Nodes along the optimal path will be used rapidly, burn out energy aggressively and eventually die hastily creating communication holes in network. This brings rapid change in the topology resulting in increased latency, poor connectivity and production of heterogeneous subnets. Therefore, utilizing suboptimal paths is encouraged for load balancing among sensor nodes. We unmitigated our efforts to augment the node life time in sensor network by frequent use of suboptimal paths, and reducing redundant sensory network traffic. Towards this end, we propose an agent-based routing approach that incorporates static and mobile agents. Static agent is responsible for calculating and maintaining the set of optimal paths. Mobile agent accounts for performing data processing and making data aggregation decisions at nodes in the network rather than bring data back to a central processor (sink). To demonstrate the performance evaluation, a prototype of a simulator is implemented.