Data-bundling is a useful technique that decreases the delivery delay of packet streams when they are transmitted over noisy channels and are subject to retransmission-based error control. In this ...paper, we investigate the packet delay statistics for a fully reliable selective repeat automatic repeat request (SR ARQ) where a data-bundling mechanism is employed. In more detail, we discuss a model for data-bundling to analyze the SR ARQ mechanism over wireless channels based on Markov chains. We evaluate various channel error distributions and analyze the buffer occupancy to check if the data-bundling mechanism provides efficient results. We further analyze the queueing, delivery and overall delay statistics at link layer. We found that using data-bundling can improve the delay performance of the SR ARQ mechanism, especially when bursty channels with heavily correlated errors are considered. Thus, this technique can bring useful improvements for real-time services, multimedia, and other delay-sensitive applications over wireless networks.
In Next Generation (NG) Wireless Networks, end-user is supported with more technologies. Each of the network system has its own characteristic. To utilize best features of each network system, a new ...architecture “Enhanced Architecture for ubiquitous Mobile Computing” has been introduced. Furthermore, load-balancing algorithms have been introduced in this architecture. These algorithms will run after a specified amount of time and all NIAs will broadcast load request to update the load values on each of the NIA in the database. Mathematical performance analysis has been carried out to prove the need for the new architecture and its algorithms.
Video users in a multicast group may be highly heterogeneous in terms of individual channel conditions and requirements for video transmission, making it a challenging task for the network to ...optimally configure the resource management. In this paper, we consider a mathematical model for the choice of the optimum number of transmission opportunities, based on a Markov chain representation of the wireless channel, where each channel state is associated to a different quality corresponding to a choice of video layer and Modulation and Coding Scheme (MCS). In case of multicast transmissions, the selection of the video layer is based on the aggregate channel conditions of all users and a collection of coordination rules. We evaluate how the cross-layer optimisation performs and we also define a taxonomy of user quality perception. We further investigate how users' satisfaction levels vary in the multicast session. Performance evaluation results show that cross-layer optimisation significantly outperforms sequential and independent scheme for multicast video transmissions, conforming the strong need for cross-layer solutions in video transmission, however, this improvement is heavily related to the resource allocation policy of the operator.
Users of video multicast groups are highly heterogeneous in terms of individual channel conditions and requirements for video transmission. Their experienced quality may vary, making it a challenging ...task for the network to optimally configure the resource management. In this paper, we consider mathematical model to represent layered video content delivery in a multicast group. We compare various network policies to choose the optimum number of transmit opportunities and we investigate the role of feedback, which, if present, dynamically tunes the resource management. We analyze the actual perceived quality of the users as well as how their satisfaction levels vary in the multicast session. Simulation results show that the presence of feedback generally enhances the overall users quality; however, this improvement is heavily related to the resource allocation policy of the operator.
Applications like inter data-centre synchronisation or client-to-cloud backups require a reliable end-to-end data transfer, however, they typically do not have strong capacity or latency constraints, ...just a loose delivery deadline. Besides, their potential to disrupt more quality-constrained flows should be kept to a minimum. These applications could be well served by a transport protocol providing a less-than-best-effort (LBE) or scavenger service rather than TCP but, neither TCP nor standard LBE methods like LEDBAT consider any notion of deadline or completion time. TCP simply tries to maximise the use of available capacity, while LEDBAT tries to enforce an LBE behaviour regardless of any timeliness requirements. This paper introduces a framework for adding both LBE behaviour and awareness of "soft" delivery deadlines to any congestion control (CC) algorithm, whether loss-based, delay-based or explicit signaling-based. This effectively allows it to turn an arbitrary CC protocol into a scavenger protocol that dynamically adapts its sending rate to network conditions and remaining time before the deadline, to balance timeliness and transmission aggressiveness. Network utility maximization (NUM) theory provides a solid foundation for the proposal. The effectiveness of the approach is validated by numerical and simulation experiments, with TCP Cubic and Vegas used as examples.
In this paper, we perform meta-analysis of leading publications in the communication area to dig out the exhausted and least investigated areas within the umbrella of Multimedia quality provisioning. ...We aggregate the result trends according to an original subject taxonomy, as well as several other relevant classifications (scenario, approach followed, and so on). The main motivation behind this work is to gather information and possibly identify the future research trends on this very important area.
The game Pokémon Go has received tremendous attention across the globe since July 2016 as a location-based augmented reality game. However, an important element of the game, namely "Gym battles", ...periodically stagnate because of several influencing factors, including non-optimally managed gameplay. A key factor of such stagnation is an imbalance between the three different groups of players called teams. In this paper, we analyze how Gym ownership is distributed among the three teams, and explore how the game dynamics can change the distribution of the Gyms among the teams. We propose a model based on an analytical framework to find the equilibrium regarding the fair distribution of Gym ownership among all the teams in a certain geographic area. We also discuss the possibility of applying strategies that can change the game dynamics in such a way that stagnation can be mitigated.
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