Optimal Node scheduling for Integrated Connected-Coverage in Wireless Sensor Networks

Wireless sensor hubs generally consist of three main parts, communication subsystem, processing subsystem and sensing subsystem, normally communication subsystem consume most of energy of a typical sensor node and this is as much energy that we can neglect the processing energy consumption. Energy consumption of the sensing subsystem depends on specific sensor type. Usually it's also much less than communication subsystem. Therefore in energy conservation scheme we generally consider only communication subsystem and neglect the sensing and processing subsystems. Energy conservation schemes can be categorized in three main groups: duty-cycling and data-driven approaches, and as the mobility management. Duty-cycling considers different activity scheduling approaches to minimize the communication subsystem energy consumption; data-driven approach considers the ways to minimize sensing subsystem energy consumption such as data aggregation or energy efficient data acquisition and transmission. While when the nodes are mobile or we have some mobile node among sensors we can use some mobility management techniques to reduce the corresponding power consumption. In this work we will focus on duty-cycling, duty-cycling is divided to two main categories which are topology control and power management. Topology control is referred to using node redundancy for sensing or communication subsystem when we have more node than sufficient to achieve desired level of connectivity or coverage in the network. Some of the work in the area of topology control has considered only connectivity of the network in the other hand some of them considered only coverage of the network and some considered both coverage and connectivity into account, some of corresponding algorithms are centralized algorithms, and some are distributed. Centralize algorithm is a type of network protocol when all data from nodes are gathered in a main node and node sleep scheduling is decided in this node then the schedules are send to the network nodes. On the other hand in distributed protocol each node decide by itself to remain active or not, or in some cases nodes sleep scheduling is done by means of local cluster heads. In this work our focus is the coverage problem of target area that occurs as the result of random and dense deployment of sensor nodes. The coverage problem indicates a disorganized placement of sensor nodes with plenty of sensing redundancy. It challenges the wireless sensor network in terms of energy and sensing efficiency. We have proposed a node scheduling solution that solves the coverage and connectivity problem in sensor networks in a integrated manner. In this way we will divide network lifetime to some specified number of rounds and in each round we will generate a coverage bitmap of sensors of the domain and based on this bitmap it will be decided which sensors remain active or go to sleep. We will check the connection of the graph by using Laplacian of adjacency graph of active nodes in each round. Also by using Minkowski technique in generation of coverage bitmap, the network will be capable of producing desired percentage of coverage. We will define the connected coverage problem as an optimization problem which is NP-compete problem and therefore we will seek a solution for the problem by GA Heuristic optimization methods in centralized fashion.