Two-Hop Routing with Traffic-Differentiation for QoS Guarantee in Wireless Sensor Networks

This paper proposes a Traffic-Differentiated Two-Hop Routing protocol for Quality of Service (QoS) in Wireless Sensor Networks (WSNs). It targets WSN applications having different types of data traffic with several priorities. The protocol achieves to increase Packet Reception Ratio (PRR) and reduce end-to-end delay while considering multi-queue priority policy, two-hop neighborhood information, link reliability and power efficiency. The protocol is modular and utilizes effective methods for estimating the link metrics. Numerical results show that the proposed protocol is a feasible solution to addresses QoS service differenti- ation for traffic with different priorities.Comment: 13 page

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

Unified clustering and communication protocol for wireless sensor networks

In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

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

Secure Routing in Wireless Mesh Networks

Wireless mesh networks (WMNs) have emerged as a promising concept to meet the challenges in next-generation networks such as providing flexible, adaptive, and reconfigurable architecture while offering cost-effective solutions to the service providers. Unlike traditional Wi-Fi networks, with each access point (AP) connected to the wired network, in WMNs only a subset of the APs are required to be connected to the wired network. The APs that are connected to the wired network are called the Internet gateways (IGWs), while the APs that do not have wired connections are called the mesh routers (MRs). The MRs are connected to the IGWs using multi-hop communication. The IGWs provide access to conventional clients and interconnect ad hoc, sensor, cellular, and other networks to the Internet. However, most of the existing routing protocols for WMNs are extensions of protocols originally designed for mobile ad hoc networks (MANETs) and thus they perform sub-optimally. Moreover, most routing protocols for WMNs are designed without security issues in mind, where the nodes are all assumed to be honest. In practical deployment scenarios, this assumption does not hold. This chapter provides a comprehensive overview of security issues in WMNs and then particularly focuses on secure routing in these networks. First, it identifies security vulnerabilities in the medium access control (MAC) and the network layers. Various possibilities of compromising data confidentiality, data integrity, replay attacks and offline cryptanalysis are also discussed. Then various types of attacks in the MAC and the network layers are discussed. After enumerating the various types of attacks on the MAC and the network layer, the chapter briefly discusses on some of the preventive mechanisms for these attacks.Comment: 44 pages, 17 figures, 5 table

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial