Luca Paladina

A multi-sink swarm-based routing protocol for Wireless Sensor Networks

Wireless sensor networks are a new emerging area where swarm intelligence can be applied with interesting implications. In fact, a strong analogy between unicellular organism colonies and wireless sensor networks can be emphasized: a sensor network can be viewed as a “colony” of simple, scarce resource nodes that, autonomously, are able only to perform simple tasks, but all together can accomplish very complex problems. In this paper we propose a routing protocol for multisink Wireless Sensor Networks with interesting properties: self organization, fault tolerance and environmental adaptation. The proposed protocol was inspired by the well known behavior (in artificial life studies) of “Slime Mold”. Such colony of unicellular organisms organizes itself in clusters by pheromone generation and evaporation mechanisms. In a similar manner our protocol manages the data traffic towards multiple sink nodes using the gradient concept and reaching high levels of autonomy and fault tolerance. We analyze the proposed protocol to examine the performances, the signalling overhead and the adaptation properties to environmental changes or nodes faults using simulation techniques.

Self Organizing Maps for Distributed Localization in Wireless Sensor Networks

Providing an efficient localization system is one of the most important goals to be pursued if an efficient utilization of sensor networks has to be addressed. This paper proposes a novel localization system based on Kohonen s self organizing maps (SOMs), able to provide some Artificial Intelligence features to sensor nodes. A SOM is a particular neural network that learns to classify data without any supervision. In each sensor node, a SOM is implemented to evaluate the sensor node position, using a very little amount of storage and computing resources. In a scenario where thousands of sensor nodes are placed, this system evaluates the position of each sensor in a distributed manner, assuming a very little percentage of nodes knowing their actual position.

Artificial Intelligence and Synchronization in Wireless Sensor Networks

The basic concept behind a Wireless Sensor Network is to deploy a large number of sensor nodes able to acquire and process data. Most of WSNs applications require sensor nodes to maintain local clocks both to determine the events order and to provide temporal information to measured data. Thus, providing a powerful synchronization system is one of the most important goals to be pursued if an efficient utilization of sensor networks has to be addressed. In order to achieve this goal, applications generally require a synchronization precision close to Milli seconds. This paper proposes a novel synchronization system based on Kohonens Self Organizing Maps (SOMs), able to provide some Artificial Intelligence features to sensor nodes. A SOM is a particular neural network that learns to classify data without any supervision. In each sensor node, a SOM is implemented to evaluate the sensor node time, using a very little amount of storage and computing resources. In a scenario where thousands of sensor nodes are placed, this system evaluates the time of each sensor in a distributed manner, assuming a very little percentage of nodes knowing their actual time, thus ensuring an effective clock synchronization among all the sensors.

Call admission control in hierarchical mobile networks

Mobile networks are requested to provide several added value services with different QoS levels. An efficient call admission control (CAC) is one of the strategic components that a network management policy requires, which defines how to allocate network resources to roaming and new users. We assume a hierarchical network architecture constituted of several cellular IP regions which may communicate each other accessing the Internet through a Mobile IP protocol. In such scenario, we demonstrate the importance of CAC not only in the ingress wireless points, but in the wired network too. An integrated approach to CAC is then proposed whose advantages are shown through simulation analysis.

A Bio-inspired Distributed Routing Protocol for Wireless Sensor Networks: Performance Evaluation

Sensor networks are wireless networks with peculiar properties that require specific attention to be properly managed if their performance and dependability have to be taken care of. In fact, both the usually hard environmental conditions where sensors are deployed and the scarcity of node resources determine overall critical working conditions that dramatically impact on parameters such as reliability, fault tolerance, power consumption and scalability. Currently available routing protocols hardly meet all these constraints, because they are not designed in a strong distributed fashion. Swarm intelligence is a science that studies the behavior of social insects characterized by distributed elaboration features, simple computational capacity, flexibility and robustness. In this paper, we propose a routing algorithm based on swarm intelligence, named pheromone protocol (PH-protocol), with some interesting features such as self organization, fault tolerance and environmental adaptation capabilities. To highlight these properties we compared our algorithm against the directed diffusion one, a well known sensor network routing protocol, and measured their performances in terms of reliability, fault tolerance, power consumption and scalability. The obtained results demonstrate that sensor networks greatly benefit from the distributed nature of our PH-protocol, which ensures interesting performance and reliability features.

Advantages in synchronization for wireless sensor networks

Providing efficient mechanisms to reduce consuming power and optimize computing resources is one of the most important goals to be pursued when an efficient utilization of sensor networks has to be addressed. To reduce power consumption at the MAC level, sensor networks usually make use of a scheduled contention protocol that adopts listen/sleep cycles. Cycles synchronization can improve performance, although in a sensor network with hundreds of nodes a predefined synchronization degree will determine a huge power consumption due to messages overhead. This paper aims to analyze advantages and disadvantages of cycles synchronization. It provides some rules that help to select and configure a MAC level protocol or a synchronization algorithm with the aim to maximize the network performance.

Resource reservation in mobile wireless networks

Resource reservation in wired networks is a relatively mature area, with some available solutions already on the market. Due to the increasingly growing diffusion of mobile terminals and services, the study of the issues concerning the management of mobility in IP-based networks is also arising increasing interest. The combination of both issues is however still at its initial definition. This work is based on the idea of combining mobile architectures with the available techniques for resource reservation. In particular, we have created a cellular IP-based architecture, which can assure some agreed levels of QoS (for instance, in terms of data throughput) according to the IP layer. We present the proposed architecture, describe its implementation and show some experimental results for its validation.

Self Organizing Maps for Synchronization in Wireless Sensor Networks

Providing a powerful synchronization system is one of the most important goals to be pursued if an efficient utilization of sensor networks has to be addressed. The basic concept behind a Wireless Sensor Network is to deploy a large number of sensor nodes able to acquire and process data. Most of WSNs applications require sensor nodes to maintain local clocks both to determine the events order and to provide temporal information to measured data; to achieve this goal applications generally require a low synchronization precision, close to Milli seconds. This paper proposes a novel synchronization system based on Kohonens Self Organizing Maps (SOMs), able to provide some Artificial Intelligence features to sensor nodes. A SOM is a particular neural network that learns to classify data without any supervision. In each sensor node, a SOM is implemented to evaluate the sensor node time, using a very little amount of storage and computing resources. In a scenario where thousands of sensor nodes are placed, this system evaluates the time of each sensor in a distributed manner, assuming a very little percentage of nodes knowing the actual time, thus ensuring an effective clock synchronization among all the sensors.

Efficient CAC in Broadband Wireless Access Networks based on Hierarchical Structures

To provide an efficient Call Admission Control (CAC) is one of the most important goals to be pursued if an efficient allocation of network resources to roaming and new users has to be addressed. Hierarchical network architectures are a common choice to build Broadband Wireless Access (BWA) networks able to provide added value services with different QoS levels. In a scenario where mobile hosts access the network via a wireless channel and are gated to the Internet through a hierarchical structure, this work aims to evidence the importance of an accurate design of the hierarchical network topology to obtain an efficient CAC process.