The random linear network coding was proposed as an adoptable coding technique for many practical communication networks. This study focuses on analysing the failure probabilities of random linear network coding to study its performance for multicast network, emphatically some known upper bounds of the failure probabilities have been improved and the worst cases are indicated for these bounds. Besides, if the more network topology information is achieved, the better upper bounds can be obtained. Furthermore when the field size goes to infinity the limit behaviours of the failure probabilities are discussed.

In recent years, a lot of work has been done in an effort to incorporate swarm intelligence (SI) techniques in building an adaptive routing protocol for mobile ad-hoc networks (MANETs). As centralised approach for routing in MANETs lack in scalability and fault-tolerance, SI technique gives natural solutions through distributed approach to the adaptive routing for MANETs. The mobile nodes (MNs) found in existing MANETs are capable of monitoring the network status as well as data processing. Thus, the MANET can be made context aware with the help of MNs local monitoring capability. In the present work, a novel mobility aware bio inspired routing protocol for MANETs referred to as mobility aware-Termite (MA-Termite) is proposed. The objectives of the proposed protocol are twofold. (1) To find the reliable path based on the stable nodes in terms of its mobility with the help of the local monitoring capability of nodes. (2) To mitigate the measurement bias using pheromone smoothing. The proposed MA-Termite is implemented in NS-2 and the results are compared with other state-of-the-art bio inspired and non-bio inspired routing protocols for its evaluation. The MA-Termite results are found to be convincing against its competing protocols in the carried out simulations.

In recent years, following the deployment of wavelength division multiplexing networks, fault detection and localisation has become a challenging issue in networks with high reliability. Optical layer monitoring schemes based on monitoring trails (m-trail) are considered an efficient way to localise a single fault unambiguously in all-optical networks. In spite of the extensive work on the m-trail concept, the issue has not been validated from the feasibility point of view. Previous works on the m-trail monitoring scheme have focused mainly on algorithm design for minimising the number of monitors, however, none of them have observed that length limitations should be considered as well. The authors investigate the physical constraints of launching m-trails, mainly focusing on the maximum length that each m-trail may have and describe an algorithm that solves the length constrained m-trail formulation problem. Numerous simulations were implemented in a physical layer simulator for observing qualitative parameters in different m-trail lengths. The authors propose 15 000 km as a length limit for each m-trail for out-of-band monitoring. Finally, an algorithmic solution is provided for monitoring trail design problem satisfying these physical constraints.

IEEE 802.11 is the most popular wireless local area network (WLAN) standard in use. WLANs support broadband multimedia communication and hence providing quality of service requirements such as good throughput and minimum end-to-end delay are the two main challenging issues in designing of WLAN protocols for supporting real-time applications. Until now, several Markov chain models have been developed to evaluate and to enhance the performance of the IEEE 802.11 distributed coordination function (DCF) protocol. However, these models cannot accurately predict the performance of the network. Also, the existing models suffer with high packet collisions resulting in degradation of throughput and end-to-end delay particularly under congested environments. This study proposes an exact Markov chain model to accurately predict the performance of the wireless networks. To alleviate the collisions and to avoid channel capture effect, the authors introduce a post-backoff stage to provide inter packet backoff (IPB) delay between successive packet transmissions. The analysis is carried out by considering the non-saturated traffic and the impact of channel errors because of Rayleigh fading. Results show significant improvement in throughput and reduction in delay using the proposed model when compared with the existing models.

Global connectivity, at anyplace and anytime, to provide high-speed, high-quality and reliable communication channels, is now becoming a reality. The credit mainly goes to the recent technological advances in wireless communications, which consist of a wide range of technologies and applications to fulfil the particular needs of end-users in different deployment scenarios (Bluetooth, Wi-Fi, WiMAX and third generation/fourth generation cellular systems). In such a heterogeneous wireless environment, one of the key ingredients to provide efficient ubiquitous computing is the design of intelligent handoff algorithms, which select the optimal target network. This study presents a novel approach for the design and implementation of a multi-criteria vertical handoff decision algorithm for heterogeneous wireless networks to achieve seamless mobility while maximising end-users’ satisfaction. Two important modules are designed; the first module estimates the necessity of handoffs and the second module selects the best network as the target of handoff. Several parallel fuzzy logic controllers with reduced rule sets are used, in combination with a fuzzy ranking algorithm, to implement these modules. Simulation results are provided and compared with a benchmark for different evaluation metrics.

The social computing, such as social networking services (SNSs) and social Networking Platforms (SNPs) provide a coherent medium through which people can be interactive and socialize. The SNP is a Web-based social space, specifically designed for end user-driven applications that facilitate communication, collaboration and sharing of the knowledge through a variety of SNSs, such as text, video and audio streams. In the conventional SNPs, such as Facebook, LinkedIn and MySpace, computers are not capable of acquiring the information based on the common intelligence and human behaviour. This survey provides a comprehensive overview of the current SNSs and discusses different possibilities of incorporating the existing SNSs into the context-aware techniques that include semantic Web, social search and social recommendations. The context-aware computing provides services customisation based on the individual human characteristics, such as human preferences, mood, behaviours, and emotions. The Integration of contextual information with SNSs can be more useful and productive for the development of the intelligent social communicational services. This survey provides several possible future research directions especially in the field of social search and recommendation that can provide better social communication capabilities. Moreover, this study will provide new directions to the future researcher for designing future generation context-based SNSs that provide services based on the on-demand collaboration.