Energy conservation is vital to wireless sensor networks (WSNs) in light of the inherently limited sensor power budget and the need for massive deployment of low-cost sensor nodes. One major source of power consumption is the challenging WSN routing mechanism. The density of sensor deployment in the field is profoundly critical to routing and the network power budget. Due to the nature of WSNs, the challenge of energy conservation takes priority over other performance metrics.

This paper is concerned with the lifetime of WSNs. The authors advance the solution of the known mixed-integer linear programming (MILP) model. They introduce a more practically applicable, efficient, and accurate mathematical optimization model called “sensor location, activity scheduling, mobile sink, and data routing problem” (SAMDP, which is defined by the authors on page 21). Their new model integrates sensor deployment, activity scheduling, and data/mobile sink routing decisions for larger-sized networks. They then propose two practical heuristics for the solution of their new mathematical model, and experimentally demonstrate their efficiency and accuracy on a large set of randomly generated test problems. Their work is very useful and different from their peers, and might be used as an initial step toward optimal WSN design. They have a very thorough, novel, and well-thought-out mathematical design.

Although their mathematical solution is very comprehensive, it remains unclear if it considers some other dynamics and design factors in the WSN field, such as: new types of mobile WSNs (such as body area networks); the dissemination of sink-node location to other nodes; different WSN media access control (MAC) protocols; and the node density as a function of different WSN application parameters.