Energy efficient organization and modeling of wireless sensor networks

With their focus on applications requiring tight coupling with the physical world, as opposed to the personal communication focus of conventional wireless networks, wireless sensor networks pose significantly different design, implementation and deployment challenges. Wireless sensor networks can be used for environmental parameter monitoring, boundary surveillance, target detection and classification, and the facilitation of the decision making process. Multiple sensors provide better monitoring capabilities about parameters that present both spatial and temporal variances, and can deliver valuable inferences about the physical world to the end user. In this dissertation, the problem of the energy efficient organization and modeling of dynamic wireless sensor networks is investigated and analyzed. First, a connectivity distribution model that characterizes the corresponding sensor connectivity distribution for a multi-hop sensor networking system is introduced. Based on this model, the impact of node connectivity on system reliability is analyzed, and several tradeoffs among various sleeping strategies, node connectivity and power consumption, are evaluated. Motivated by the commonality encountered in the mobile sensor wireless networks, their self-organizing and random nature, and some concepts developed by the continuum theory, a model is introduced that gives a more realistic description of the various processes and their effects on a large-scale topology as the mobile wireless sensor network evolves. Furthermore, the issue of developing an energy-efficient organization and operation of a randomly deployed multi-hop sensor network, by extending the lifetime of the communication critical nodes and as a result the overall network\u27s operation, is considered and studied. Based on the data-centric characteristic of wireless sensor networks, an efficient Quality of Service (QoS)-constrained data aggregation and processing approach for distributed wireless sensor networks is investigated and analyzed. One of the key features of the proposed approach is that the task QoS requirements are taken into account to determine when and where to perform the aggregation in a distributed fashion, based on the availability of local only information. Data aggregation is performed on the fly at intermediate sensor nodes, while at the same time the end-to-end latency constraints are satisfied. An analytical model to represent the data aggregation and report delivery process in sensor networks, with specific delivery quality requirements in terms of the achievable end-to-end delay and the successful report delivery probability, is also presented. Based on this model, some insights about the impact on the achievable system performance, of the various designs parameters and the tradeoffs involved in the process of data aggregation and the proposed strategy, are gained. Furthermore, a localized adaptive data collection algorithm performed at the source nodes is developed that balances the design tradeoffs of delay, measurement accuracy and buffer overflow, for given QoS requirements. The performance of the proposed approach is analyzed and evaluated, through modeling and simulation, under different data aggregation scenarios and traffic loads. The impact of several design parameters and tradeoffs on various critical network and application related performance metrics, such as energy efficiency, network lifetime, end-to-end latency, and data loss are also evaluated and discussed

Energy aware topology control protocols for wireless sensor networks

Wireless Sensor Network has emerged as an important technology of the future due to its potential for application across a wide array of domains. The collaborative power of numerous autonomousremote sensing nodes self configured into a multi hop network permits in-depth accurate observation of any physical phenomenon. A stringent set of computational and resource constraints make the design and implementation of sensor networks an arduous task. The issue of optimizing the limited and often non-renewable energy of sensor nodes due to its direct impact on network lifetime dominates every aspect of wireless sensor networks. Existing techniques for optimizing energy consumption are based on exploiting node redundancy, adaptive radio transmission power and topology control. Topology control protocols significantly impact network lifetime, routing algorithms and connectivity. We classify sensor nodes as strong and weak nodes based on their residual energy and propose a novel topology control protocol (NEC) which extends network lifetime while guarantying minimum connectivity. Extensive simulations in Network-Simulator (ns-2) show that our protocol outperforms the existing protocols in terms of various performance metrics. We further explore the effectiveness of data aggregation paradigm as a solution to the dominant problem of maximizing energy utilization and increasing network bandwidth utilization in sensor networks. We propose a novel energy efficient data aggregation protocol based on the well-known k-Means algorithm. Our protocol achieves energy efficiency by reduced number of data transmissions at each level of a hierarchical sensor network. Our protocol exploits the spatial and temporal coherence between the data sensed by neighboring sensor nodes in a cluster to reduce the number of packet transmissions. Sensor nodes apply k-Means algorithm to the raw data to generate a reduced set of mean values and forward this modified data set to cluster-head nodes. We further prove the effectiveness of our protocol in providing increased energy conservation in the network by extensive simulation results

Strategi Efisiensi Wireless Sensor Network (WSN)

Abstrak: Wireless Sensor Network adalah teknologi yang berkembang pesat yang menawarkan potensi luar biasa untuk merevolusi banyak industri dan bidang. Wireless Sensor Network menjadi semakin populer karena keserbagunaannya, biaya yang rendah serta kemudahan dalam penerapannya. Terlepas dari keunggulan tersebut, masih ada beberapa tantangan yang perlu diatasi untuk mencapai kinerja tinggi dalam WSN yang terdistribusi secara total. Tujuan dari penelitian ini adalah menyajikan strategi ataupun solusi kepada user dalam kaitannya mencapai atau meningkatkan kinerja WSN yang berdampak pada keberhasilan pengumpulan data. Studi empiris dari peneliti-peneliti terkait menjadi metode pilihan yang digunakan.. Terdapat dua strategi yang diajukan untuk mencapai dan meningkatkan efisiensi WSN yaitu dengan pengoptimalan topologi jaringan sensor nirkabel dan memanfaatkan mode tidur. Adapun langkahnya dengan merencanakan penerapan node sensor, mengoptimalkan konsumsi energi melalui perutean yang efisien dan teknik agregasi data, mempertimbangkan skalabilitas dan lokalisasi, serta menggabungkan toleransi kesalahan dan ketahanan, jaringan dapat mencapai keseimbangan antara cakupan, konektivitas, efisiensi energi, dan ketahanan. Kata kunci: wireless sensor network, efisiensi, topologi jaringan, mode tidur jaringan.   Abstract: Wireless Sensor Networks are a rapidly evolving technology that offers tremendous potential to revolutionize many industries and fields. Wireless sensor networks are becoming increasingly popular because of their versatility, low cost and ease of implementation. Despite these advantages, there are still some challenges that need to be overcome to achieve high performance in a totally distributed WSN. The purpose of this study is to present strategies or solutions to users in relation to achieving or improving WSN performance which has an impact on the success of data collection. Empirical studies from related researchers are the method of choice used. There are two strategies proposed to achieve and improve WSN efficiency, namely by optimizing the wireless sensor network topology and utilizing sleep mode. The steps are by planning the implementation of sensor nodes, optimizing energy consumption through efficient routing and data aggregation techniques, considering scalability and localization, and combining fault tolerance and robustness, the network can achieve a balance between coverage, connectivity, energy efficiency, and resilience. Keywords: wireless sensor network, efficiency, network topology, network sleep mode

An objective based classification of aggregation techniques for wireless sensor networks

Wireless Sensor Networks have gained immense popularity in recent years due to their ever increasing capabilities and wide range of critical applications. A huge body of research efforts has been dedicated to find ways to utilize limited resources of these sensor nodes in an efficient manner. One of the common ways to minimize energy consumption has been aggregation of input data. We note that every aggregation technique has an improvement objective to achieve with respect to the output it produces. Each technique is designed to achieve some target e.g. reduce data size, minimize transmission energy, enhance accuracy etc. This paper presents a comprehensive survey of aggregation techniques that can be used in distributed manner to improve lifetime and energy conservation of wireless sensor networks. Main contribution of this work is proposal of a novel classification of such techniques based on the type of improvement they offer when applied to WSNs. Due to the existence of a myriad of definitions of aggregation, we first review the meaning of term aggregation that can be applied to WSN. The concept is then associated with the proposed classes. Each class of techniques is divided into a number of subclasses and a brief literature review of related work in WSN for each of these is also presented

Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks

In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.Comment: To appear in Journal of Computer and System Science