Multimedia Content Distribution in Hybrid Wireless Networks using Weighted Clustering

Fixed infrastructured networks naturally support centralized approaches for group management and information provisioning. Contrary to infrastructured networks, in multi-hop ad-hoc networks each node acts as a router as well as sender and receiver. Some applications, however, requires hierarchical arrangements that-for practical reasons-has to be done locally and self-organized. An additional challenge is to deal with mobility that causes permanent network partitioning and re-organizations. Technically, these problems can be tackled by providing additional uplinks to a backbone network, which can be used to access resources in the Internet as well as to inter-link multiple ad-hoc network partitions, creating a hybrid wireless network. In this paper, we present a prototypically implemented hybrid wireless network system optimized for multimedia content distribution. To efficiently manage the ad-hoc communicating devices a weighted clustering algorithm is introduced. The proposed localized algorithm deals with mobility, but does not require geographical information or distances.Comment: 2nd ACM Workshop on Wireless Multimedia Networking and Performance Modeling 2006 (ISBN 1-59593-485

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

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

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

Collision-free Time Slot Reuse in Multi-hop Wireless Sensor Networks

To ensure a long-lived network of wireless communicating sensors, we are in need of a medium access control protocol that is able to prevent energy-wasting effects like idle listening, hidden terminal problem or collision of packets. Schedule-based medium access protocols are in general robust against these effects, but require a mechanism to establish a non-conflicting schedule. In this paper, we present such a mechanism which allows wireless sensors to choose a time interval for transmission, which is not interfering or causing collisions with other transmissions. In our solution, we do not assume any hierarchical organization in the network and all operation is localized. We empirically show that our localized algorithm is successful within a factor 2 of the minimum necessary time slots in random networks; well in range of the expected (worst case) factor 3-approximation of known first-fit algorithms. Our algorithm assures similar minimum distance between simultaneous transmissions as CSMA(/CD)-based approaches