A new QoS routing algorithm based on self-organizing maps for wireless sensor networks

For the past ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore and compare the performance of two very well known routing paradigms, directed diffusion and Energy- Aware Routing, with our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Using artificial intelligence in routing schemes for wireless networks

For the latest 10 years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well-known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Giving Neurons to Sensors: An Approach to QoS Management Through Artificial Intelligence in Wireless Networks

For the latest ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, selforganizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Parallel Processing for Range Assignment Problem in Wireless Sensor Networks

Wireless sensor network is a collection of autonomous devices called sensor nodes which sense the environmental factors such as temperature, pressure, humidity, moisture, etc. The nodes sense the data, process it and transmit to the other nodes within their transmission range through radio propagation. Energy minimization in wireless sensor networks is a significant problem since the nodes are powered by a small battery of limited capacity. In case of networks with several thousand nodes, the simulation of algorithms can be very slow. The parallel computing model provides significantly faster simulation time for larger networks. Parallel processing involves executing the program instructions by dividing them among multiple processors with the objective of reducing the running time. So, we propose algorithms for the range assignment problem in wireless sensor networks using the parallel processing techniques. We also discuss the complexity of the proposed algorithms and significance of the parallel processing techniques in detail. The proposed techniques will be useful for implementing the distributed algorithms in WSNs

Wireless Sensor Networks (WSNs): Security and Privacy Issues and Solutions

Wireless sensor networks (WSNs) have become one of the current research areas, and it proves to be a very supportive technology for various applications such as environmental-, military-, health-, home-, and office-based applications. WSN can either be mobile wireless sensor network (MWSN) or static wireless sensor network (SWSN). MWSN is a specialized wireless network consisting of considerable number of mobile sensors, however the instability of its topology introduces several performance issues during data routing. SWSNs consisting of static nodes with static topology also share some of the security challenges of MWSNs due to some constraints associated with the sensor nodes. Security, privacy, computation and energy constraints, and reliability issues are the major challenges facing WSNs, especially during routing. To solve these challenges, WSN routing protocols must ensure confidentiality, integrity, privacy preservation, and reliability in the network. Thus, efficient and energy-aware countermeasures have to be designed to prevent intrusion in the network. In this chapter, we describe different forms of WSNs, challenges, solutions, and a point-to-point multi-hop-based secure solution for effective routing in WSNs

SensoTrust: trustworthy domains in wireless sensor networks

Wireless sensor networks (WSNs) based on wearable devices are being used in a growing variety of applications, many of them with strict privacy requirements: medical, surveillance, e-Health, and so forth. Since private data is being shared (physiological measures, medical records, etc.), implementing security mechanisms in these networks has become a major challenge. The objective of deploying a trustworthy domain is achieving a nonspecific security mechanism that can be used in a plethora of network topologies and with heterogeneous application requirements. Another very important challenge is resilience. In fact, if a stand-alone and self-configuring WSN is required, an autosetup mechanism is necessary in order to maintain an acceptable level of service in the face of security issues or faulty hardware. This paper presents SensoTrust, a novel security model for WSN based on the definition of trustworthy domains, which is adaptable to a wide range of applications and scenarios where services are published as a way to distribute the acquired data. Security domains can be deployed as an add-on service to merge with any service already deployed, obtaining a new secured service

Optimized transmission and selection designs in wireless systems

University of Technology Sydney. Faculty of Engineering and Information Technology.Most modern wireless communication systems are hierarchical complex systems which consist of many levels of design elements and are subject to limited resources (e.g. power or bandwidth). Thanks to numerous newly-introduced devices in different forms such as sensors and relays and the integration of multiple antennas, spectral efficiency and reliability of wireless transmission could be significantly improved. Nevertheless, it also becomes much more challenging to control the devices and allocate the limited resources in an optimal fashion in order to approach capacity gains. This dissertation is concerned with mixed-binary or combinatorial optimization problems to improve various service goals for a variety of interesting yet difficult wireless communication applications. These problems are highly prized for academic significance but remained open due to their mathematical challenges. We shall explore the hidden d.c. (difference of convex (or concave) functions) structure of the objective functions as well as the binary constraints. Further, we will prove such general d.c. programs can be equivalently converted into canonical d.c. programs with d.c. objective functions that are subject to convex and/or affine constraints only. Although global optimal algorithms are generally possible for such d.c. programs, they are normally very computation-intensive. Instead, we propose tailored path-following local-optimal d.c. algorithms with significantly reduced computational complexity. Through extensive simulation results, the designed d.c. decompositions of the problems are proven effective. The proposed algorithms are efficient and computationally affordable while locating outstanding solutions in comparison with other existing algorithms. In those more sophisticated problem scenarios, the d.c. algorithm appears to be the only suitable option thanks to the superior flexibility. In the first part of the thesis, we will consider a sensor network for spectrum sensing in the context of cognitive radios. To improve sensing quality and prolong the battery life of sensors, the least correlated subset of sensors needs to be selected. A new Bregman matrix deviation-based framework is shown applicable to all the concerned correlation measure functions. The second research investigates a relay-assisted multi-user wireless network. Besides the relay beamforming variables, we add into consideration a set of binary link variables which represent on/off operations of individual relays in relation to transmitter-receiver links. To achieve the maximin SNR or SINR capacity, certain relays may be optimally deactivated. This leads to reduced power consumption and complexity/ overhead of management. The relay assignment and beamforming design is a joint mixed combinatorial nonlinear program which is non-convex and non-smooth. Nonetheless, we show the it can be fit into a canonical d.c. optimization framework. Simulation results demonstrate the benefits of relay selection and beamforming. The last research stems from the study of conventional coordinated transmission design with respect to transmit covariance and precoding matrix/vector variables. Inspired by the well-known Han-Kobayashi message splitting method in 2-user SISO interference channels, we further extend the idea of message splitting to the MIMO interference networks. An innovative non-smooth rate formula is discovered which builds the foundation of the work. The design in common and private covariance matrices or beamforming vectors, as well as the pairing variables, is formulated as a joint combinatorial nonlinear program which is non-convex and non-smooth. Due to the great difficulty, it is not imminently possible to jointly handle both variables. Therefore, we first propose an intuitive heuristic pairing algorithm to find excellent pairing choices. Then, the non-convex optimization problems in covariance matrices or beamforming vector variables are dealt with in the d.c. optimization framework. Finally, simulation results reveal the great potential of the novel message splitting scheme in approaching rate capacity

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs