The Components Of Centralized Expretation In The Networking System

A WSN is a type of wireless networks that consists of collection sensor nodes which are tiny devices. Each sensor node of the network has different processing capability. It may contain multiple types of memory (program, data and flash memories), have a RF transceiver, have a power source (e.g., batteries and solar cells), and accommodate various sensors and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc fashion [13, 14]. Optimum need of each sensor node is to maximize its own utility function. Also the whole network requires resource assignments balance to perform in a useful and efficient way. This chapter presents a brief survey on WSNs showing its types, characterizing features, protocols and applications.

Network nodes can have logical or actual communication with all devices,this communication mostly defines the type of network topology, depending on the application. Sensors are able to be pair with all the topologies types but, in some cases, the sensors may not be appropriate for all the networks. Most logical network topology tends to be defined depending on their logical roles. Centralized configuration techniques are always appropriate for networks whereby the processing power capacity specifically depends on a specific but unique device. The device is responsible for coordination, processing, and management of any information activities that is sensed within the environment. From here, it forwards the grasped information to a sink node. This, therefore, means that the sensors are quite reliable in grasping information (Karl, Holger, and Willig 2005, 105). The advantage of this network arrangement is the centralized configuration allows more energy management and roaming is usually allowed inside the network to facilitate

Sensor nodes have insured wireless communication limited node capabilities. There are lots of challenges put into the sensor network. As discussed earlier WSN is definitely an infrastructure less network, therefore it communicates on the wireless network. The key challenge in WSN is the power supplied to the sensor nodes. Usually the power supplied to the sensor nodes is nonrenewable [12]. Some protocols are utilized in WSN, they are accustomed to maximize the lifetime of the network by the effective management of the power resources. The key issues are explained

Nowadays distributed systems are large and finding faults in such large system ishard. Distributed nature of those faults makes it complex to identify. Again thosefaults are often partial, irregular and may result in abnormal behavior rather thansystem failure. So diagnosing a problem in such systems require collecting relevantinformation from many different nodes and correlating those with the problem.One of the main sources of information that can give the idea about root cause of prob-lems in a distributed systems is communication information between nodes. Lookingat communication between different devices in distributed system, it is seen that thoseare operated using various protocols. Among the protocols, Border

Zhang, H., Zheng, M., Li, J., Yu, H., & Zeng, P. (2010, June). Redundancy control for reliability-lifetime tradeoff in energy harvesting wireless sensor networks. In Computer Design and Applications (ICCDA), 2010 International Conference on (Vol. 2, pp. V2-539). IEEE.

The mobile computing technology is an emerging technology, which consist of wireless sensor networks. The wireless sensor is the smallest unit of a network and some of the features supports large scale deployment, mobility, reliability and other applications. According to (Hoon-Jae, 2011), the main goals of WSNs are to deploy a number sensor devices over an unattended area and transmit to certain locations.

Sensor network protocols have a unique capability self-organizing. Another interesting feature of wireless sensor networks is that the sensor nodes cooperate with each other. Sensor nodes have an in-built processor, using which before transmission raw data is processed. These features facilitate wide range of applications of wireless sensor networks like biomedical, environmental, military, event detection and vehicular telematics.

Wireless sensor networks consists of large number of sensors which are distributed densely and partially. There are numerous number of small sensor nodes which are self-restrained which consists of sensors which performs according to the environmental conditions.

Due to limited and non-rechargeable energy provision, the energy resource of sensor networks should be managed wisely to extend the lifetime of sensors. Sensor networks have recently emerged as a platform for several important surveillance and control applications .Each sensor has an onboard radio that can be used to send the collected data to interested parties. One of the advantages of wireless sensors networks (WSNs) is their ability to operate unattended in harsh environments in which contemporary human-in-the-loop monitoring schemes are risky, inefficient and sometimes infeasible. Therefore, sensors are expected to be deployed randomly in the area of interest by a relatively uncontrolled means, e.g. dropped by a helicopter, and to collectively form a network in an ad-hoc manner. In order to achieve high energy efficiency and increase the network scalability, sensor nodes can be organized into clusters. Data collected from sensors are sent to the cluster head first, and then forwarded to the base station. Network lifetime can be defined as the time elapsed until the first node (or the last node) in the network depletes its energy (dies).

Wireless Sensor and Actor Networks (WSAN) have attracted a lot of interest in recent years. Their potential applications include search-and-rescue, forest fire detection and containment, battlefield reconnaissance, under-water surveillance, etc. In WSAN, sensors which are small, densely-populated, and power-constrained devices probe their surroundings and send the collected data to more capable nodes (actors) for processing and putting forward an appropriate response [1]. For example, sensors can detect rising heat in some spots in a forest and inform mobile robots (actors) that correlate the reports from various sensors and conclude the eruption

With increased capabilities and decreased costs, mobile wireless sensor network rapidly gained popularity and interest that greatly enhanced ability to monitor any phenomena. The idea of needs for monitoring has been around for a long time. However, a mobile wireless sensor network became available because of microelectromechanical systems and implementation of wireless communication such as satellites and GSM networks to transmit the gathered data. Further development in semiconductor technologies enabled miniaturization, low power consumption and decreased cost (Kumbhare, Rangaree, & Asutkar, 2016). Even though the monitoring with the use of sensor network have been around for a couple of decades the implementation was done more in stationary approach rather than mobile. Similarly to

In the previous section, we mainly focus on the connectivity and related survivability issues of WSNs. It is the foundation that we deploy WSNs to achieve its main objective which is to monitor the field of interest / detect desired data and it is coverage that determines whether the field of interest is under strict surveillance or not. So, in this section, we will summarize the related work on integrated connectivity and coverage problem in WSN. In [68], [69], it’s clear that connectivity only requires that the location of any active node be within the communication range of one or more active nodes such that all active nodes can form a connected communication backbone, while coverage requires all locations in the coverage region be

In many application areas, the wireless sensor network must be able to operate for long periods of time, and the energy consumption of both individual sensor nodes and the sensor network as a whole is most important. Thus energy consumption is an important issue for wireless sensor networks. Figure 1 shows the architecture of wireless sensor network. It consists of one sink node (or base station) and a (large) number of sensor nodes deployed over a

Also, we consider this connected WSN as 1-connected. Depends on the different connectivity/failure resilience requirement, the stronger types of connectivity need to be considered, i.e., k-connectivity. Based on the definition of connectivity in the graph theory, which is “it asks for the minimum number of elements (nodes or edges) that need to be removed to disconnect the remaining nodes from each other”, k-connectivity means that the network can keep its connectivity by removing at most k-1 nodes from itself. In this case, a network with k-connectivity and k>1 has much better fault tolerance/resilience than a network with only 1-connectivity. Since the nodes in a WSN could be failed randomly which are caused by battery depletion or wireless interference, preserving the k-connectivity is critical for WSN and could extend the life time of a WSN. Li et al. [6] provided a good survey on connectivity and coverage in WSNs.

Wireless sensor networks are the networks that gather information such as environmental information, which there are numbers of applications of WSN such as healthcare, building monitoring, forest fire, smart home etc. WSN is capable of sensing, processing and communicating independently. However, as most of the sensor nodes are powered by non-rechargeable battery, the limitation of energy supply has considerably reduced the lifetime of the sensor network. Hence, new designs of sensor node network and energy efficient MAC (Media Access Control) and protocols for long term autonomous monitoring wireless sensor network has become the next vision.