Research On Energy Problem Of Wireless Sensor Networks Based On Cubic And Cross-Layer Architecture

Wireless Sensor Networks is the next generation sensor networks, which integrating sensor technology, embedded computing technology, advanced networking and wireless communication technology and distributed signal information processing techniques. The sensing acquirement technology has been changed from singularity to integration, miniaturization and networking. It will realize the interconnection of physical world, computer world and human society eventually.Though many specific technical challenges remain and deserve much further study, the primary factor currently limiting progress in sensor networks is not these challenges but is instead the lack of an overall Sensor Network Architecture (SNA). Since limited processing speed, storage capacity, and communication bandwidth of sensor node, the energy consumption is the most important factor to determine the life of a sensor network. This makes energy optimization more complicated in sensor networks because it involved not only reduction of energy consumption but also prolonging the life of the network as much as possible. This can be done by having energy awareness in every aspect of design and operation through the overall SNA. Dynamic power management (DPM) can be used to reduce more energyconsumption. In addition, under the condition of full coverage and connectivity, how to reduce the energy consumption is another important issue.This paper focuses on the energy problem of wireless sensor networks and has the following researches:1. The basic idea of Cubic and Cross-Layer (CCL) sensor network architecture proposed in this thesis is combing the layering thought of OSI reference model and cross-layer design of sensor networks.In CCL, the SNA can be divided into physical layer, sensor service protocol layer (SSP) and application layer. SSP which is similar to the"narrow waist-SP"proposed by Culler, is a common abstraction as a middleware layer. All these services are considered or accessible to be in a cross-layer manner instead of being full encapsulated at one layer, only visible to the one above and below.2. The DPM policy and algorithm proposed by Sinha have been modified in this paper with considering more factors such as the battery status. In addition, the time threshold which the least time should sensor node be stayed in the sleep state is revised. The sensor network consumed less energy in our simulation than the old one. A hybrid automata model to represent our sleep state transition policy and message-driven algorithm for awakening the sleep nodes are proposed in this paper. The message-driven algorithm can effectively avoid huge energy consumption caused by to the failure of packet transmission and largely deduce the collision of the networks.3. This paper addresses the issues of maintaining sensing coverage and connectivity by keeping a minimal number of sensor nodes in the active mode in wireless sensor networks. One important issue that arises in such high-density sensor networks is density control—the function that controls the density of the working sensor set to a certain level. It is desirable to choose a minimal set of working sensors in order to reduce power consumption and prolong network lifetime. If the radio range is at least twice of the sensing range, a complete coverage of a convex area implies connectivity among the working set of nodes.This paper combines the DPM and coverage problem of sensor networks, proposes an OGDC-DPM algorithm which is a dynamic power management policy based on Optimal Geographical Density Control (OGDC). This algorithm exploits a backoff timer method, which avoids the possibility of multiple neighboring nodes volunteering themselves to be the starting node in a round. The simulation result proved that this algorithm has energy effective and hence prolong the lifetime of the sensor network.4. This paper discusses the upper bound of sensor network lifetime and the diagnosis of sensor network node. Though WSNs can be used in environment monitoring and protection, the large number of invalidated sensor nodes is a huge hazard to environment. Hence, it is the fist time to propose the environment pollution of sensor nodes in this paper. At last, several solutions to the environment pollution caused by the batteries of sensor nodes are proposes, including high energy battery, biological battery, energy self-collection and wireless recharge techniques and sensor nodes collection. The sensor nodes can be collected by using the analysis of WSNs lifetime and diagnosis technology under different application scenario.