Network Modeling and Interference Analysis in Pervasive Technology

Pervasive computing aims to create environments where the technology is invisibly integrated into. This vision is realized by means of wireless networks, i.e. cheap and small pervasively distributed devices which communicate wireless. Nowadays, these technologies are widely employed for several applications, such as accurate area monitoring and distributed information systems, where the information is directly matched to the items. The strength of a wireless network is the cooperation among nodes: in order to perform its task, a node relies on the information exchanged with other nodes. The nodes and the links of a wireless networks are easily modeled by a family of graphs called unit disk graph (UDG). The degree distribution of a unit disk graph is an important aspect for investigating the behavior of a wireless network. In the literature, several studies was focused on the degree distribution of unit disk graphs, but they lacked in precision. In Chapter 1, the degree distribution is studied with the inclusion of border effects. The achieved results are validated through simulations and compared to the state-of-the-art approaches. RFID technology is a key component in the implementation of pervasive computing. An RFID system consists of small tags containing a microchip and an antenna, readers to acquire data stored in the tags by means of radio frequency signals, and a back-end server for data processing and storage. Due to low production cost, the majority of RFID systems exploits passive tags, i.e. tags without a battery. Their simple integrated circuit is fed by the electromagnetic field emitted by the readers: passive tags operate only in response to a reader interrogation. By means of their automatic identification, physical objects can be easily mapped in an information system. Interferences among readers and tags may prevent communication. Two types of collision can be generated: the reader-to-tag collision, where a tag in the intersection of the interrogation zones of two readers is simultaneously queried by both of them, and the reader-to-reader collision, where two readers disturb each other if they are located within a specific distance called interference range. There are two types of reader collision: reader-to-tag and reader-to-reader collision. The reader-to-tag collision involves readers whose reading areas overlap. They could try to query the same tag at the same time. Although they use different frequency bands, none of them can identify the tag, since the tag has no filtering capabilities. The reader-to-reader collision prevents a reader from correctly identify tags due to the concomitant transmission of another reader. In this case, the weak response of the tags is distorted by the stronger signal of the other reader. An evaluation of the reader-to-reader collisions is often based on simple models that consider only direct collisions among two readers, like for example the unit disk graph model. Instead, more complex models capture the total signal power emitted by each reader and assume that the power of each signal decays as distance grows. Chapter 2 describes the main models of the two families and compare their accuracy. Many protocols have been proposed to reduce reader-to-reader collisions in RFID systems. The majority of them exploits Carrier Sense Multiple Access (CSMA) or Time Division Multiple Access (TDMA) scheme. Chapter 3 describes the main state-of-the-art approaches and the most effective criteria for their performance evaluation. A distinction among the protocols can be introduced according to their requirements: beside the protocols that are characterized by limited requirements, there are other protocols that require an advanced communication system. Two popular state-of-the-art TDMA protocols that use only one data channel are DCS and Colorwave. A relevant quality of DCS is its fairness, due to the opportunity to reserve a timeslot for the nodes that experience a reader-to-reader collision. Colorwave represents an evolution of DCS, and its main novelty is the introduction of an adaptable parameter. Colorwave maximizes the network throughput, since the readers with few neighbors communicate more often than the ones in denser areas. Moreover, Colorwave is suitable for networks with mobile readers, because it can manage deployment changes, avoiding performance loss. In Chapter 4, three different protocols are proposed, adopting the basic mechanisms common to DCS and Colorwave, and without introducing any additional requirements. Probabilistic Distributed Color Selection (PDCS) introduces in the collision resolution of DCS an additional parameter p, representing the probability of adopting a different behavior after the detection of a collision. Consequently, the number of collisions decreases. Moreover, this protocol allows a multichannel transmission, according to the international RFID regulations. Distributed Color Natural Selection (DCNS) is specifically developed in order to exploit a new configuration, called the Killer configuration. The goal of the proposed configuration is to generate a selfish behavior similar to the natural selection. As a result, the throughput of the network improves and the largest benefit can be get by the RFID readers chosen according to the application specification. Probabilistic Colorwave (PCW) introduces a probabilistic parameter in the collision resolution routine of Colorwave. The effects of this factor are analyzed for two different configurations: the one adopted by Colorwave and the killer configuration adopted by DCNS. With respect to the TDMA protocols that exploits one additional control channel, NFRA provides an optimal management of the readers inside the interference range (neighborhood). However, two drawbacks can be identified in this algorithm. First of all, the algorithm maximizes the throughput, privileging readers with a limited neighborhood, since they have lower probability to be overridden by close transmission. As a consequence, their frequent queries could prevent readers with a larger neighborhood from communicating. To schedule the readers for transmitting, the algorithm assigns to disabled readers the same priority of transmitting ones, so during long executions there may be significant differences among the transmissions performed by each reader. Secondly, some hardware assumptions make the implementation of NFRA in passive RFID systems hard. Two different approaches are described in Chapter 5 in order to mitigate the main drawbacks of NFRA. NFRA++ includes two techniques to improve both the fairness and the throughput of NFRA. Geometric Distribution Reader Anticollision (GDRA) exploits the Sift geometric probability distribution function to minimize reader collision problems. GDRA shows better performance than NFRA, it can be implemented in a real DRE without extra hardware and it is compliant with EPC-ETSI requirements.