Edge computing is shaping the way to run services in the Internet by allowing the computations to become available close to the user's proximity. Many implementations have been recently proposed to facilitate the service delivery in data centers and distributed networks. However, we argue that those implementations cannot fully support the operations in Community Mesh Networks (CMNs) since the network connection is highly intermittent and unreliable. In this paper, we propose PiCasso, a novel multi-access edge computing platform that combines the advances in lightweight virtualisation and Information-Centric Networking (ICN). PiCasso utilises in-network caching and name based routing of ICN to optimise the forwarding path of service delivery. We analyse the data collected from Guifi.net, the biggest CMN worldwide, to develop smart heuristic for the service deployment. Through a real deployment in Guifi.net, we show that our service deployment heuristic HANET (HArdware and NETwork Resources), improves the response time up to 53% and 28.7% for stateless and stateful services respectively. Finally, using PiCasso for the service delivery in Guifi.net, we achieve 43% traffic reduction compared to the traditional host-centric communication.

This paper presents the results of spectrum occupancy measurements carried out in three different locations in Thailand: the Pathum Thani province (suburban), Bangkok (urban), and the Mae Kasa sub-district (rural) in the Tak province using a low-cost spectrum analyzer based system to show the spectrum occupancy at UHF TV band for testing the feasibility of TV White Space (TVWS) technology. Furthermore, inaccuracy of fixed threshold setting while performing spectrum occupancy measurements is shown by comparing the data with the ground truth report from the National Broadcasting and Telecommunications Commission (NBTC). An adaptive threshold setting algorithm, namely, Forward Consecutive Mean Excision (FCME) is then applied for determining the performance while carrying out spectrum occupancy measurements. Additionally, the adaptive threshold setting is modified to improve the accuracy of spectrum detection making the resultant spectrum occupancy more reliable.

In this paper, we provide an initial evaluation of a home smart lighting system - demonstrating the advantages of ICN paradigm through the primitive features of NDN architecture. A prototype of NDN based smart home lighting was developed and benchmarked against the IP cloud based approach.

Spectrum sharing is a key function to provide fairness allocation as well as service satisfaction across multiple users in cognitive radio networks. Even though spectrum sharing can benefit from spectrum handoff to enhance rate performance by switching from unavailable channels to available ones, the negative impact on handoff delay can cause significant service degradation. In this work, we present a hybrid spectrum sharing strategy that includes novel static and dynamic spectrum sharing algorithms based essentially on a rate compensation approach and adapted best fit algorithms. The static scheme is applicable for some specific network configurations where spectrum handoff is not necessary. Conversely, the dynamic scheme can benefit from spectrum handoff to increase the achieved rate and also compensate for the lost rate from the unavailable periods. These two sharing schemes are operated adaptively according to the current network environment. We compare our hybrid strategy with a fully dynamic one and an optimization framework. The proposed hybrid spectrum sharing demonstrates its effectiveness in terms of improving the overall service satisfaction and reducing the number of handoffs while the achieved rate is fulfilling compared to the optimal.

Sharing available resources in cognitive radio networks can benefit from spectrum handoff to enhance the rate performance by switching from current unavailable channels to the available ones. However, spectrum handoff can cause transmission interruptions leading to the degradation of services. In this work, we aim to balance the tradeoff between benefits of spectrum handoff and their negative impacts on spectrum sharing. Therefore, we develop an adaptive hybrid strategy that includes novel static and dynamic spectrum sharing based essentially on a rate compensation concept. The former is suitable when spectrum handoff is not necessary. The latter allows performing spectrum handoff to compensate the lost rate from the unavailable periods and improve the rate performance. We compare our hybrid strategy with a fully dynamic one and an optimization framework. Through simulations, we show that our strategy reduces the number of handoffs significantly while the achieved rate is fulfilling compared to the optimal.

In this work, we propose a heuristic for dynamic spectrum sharing in cognitive radio networks. The concept of rate compensation is introduced so that cognitive radio users are able to achieve their rate requirement by performing adequately spectrum handoffs. Indeed, performing spectrum handoff can increase the achieved rate obtained by moving from unavailable channels to available ones. However, handoffs should also be reduced to decrease handoff delays and access contention in the network which can in turn impact the achieved rate.

In cognitive radio networks, spectrum sharing among secondary users can benefit from having more transmission opportunities through spectrum handoff. However, the spectrum sharing strategy can also increase negatively the number of performed handoffs. In this work, we study formally the impact of spectrum sharing on spectrum handoff and at the same time the impact of the spectrum handoff on the overall achievable rates from spectrum sharing. We base our study on three proposed spectrum sharing strategies: static, instantaneous and global. We show that depending on the network configuration, static and/or instantaneous can be almost as powerful as the global strategy. In case handoffs are necessary, the global strategy reduces them significantly. Furthermore, we analyze the benefits of multi-channel communications on the quality of sharing in terms of fairness, achieved rate and number of handoffs.

In Cognitive Radio Networks, secondary users are required to handoff from a wireless channel to another in order to cope with the dynamic spectrum environment imposed by primary users activity. Spectrum handoff may cause service interruptions or significant delays leading to the degradation of the quality of transmission. In this paper, we propose and study a novel spectrum handoff strategy aiming at reducing the unnecessary handoff operations while considering a delay bound requirement. First, the expected delay of application packets is computed as a function of the queue associated with a channel. This delay reflects the status of the channel and its usability for transmitting packets. Second, and in order to prevent the unnecessary handoffs, we use the expected delays to estimate a delay violation ratio that guides the spectrum handoff and selection decisions. Besides, we study the utility of using additional backup channels at the time of handoff to alleviate the problem of fast successive handoffs. We show through simulations that our strategy controls better the tradeoff between channel handoffs and achieving the delay requirement compared to random handoff and low channel occupancy handoff.