Improvement in DRX Power Saving for Non‐real‐time Traffic in LTE

A discontinuous reception (DRX) operation is included in the Long Term Evolution (LTE) system to achieve power saving and prolonged battery life of the user equipment. An improvement in DRX power saving usually leads to a potential increase in the packet delay. An optimum DRX configuration depends on the current traffic, which is not easy to estimate accurately, particularly for non‐real‐time applications. In this paper, we propose a novel way to vary the DRX cycle length, avoiding a continuous estimation of the data traffic when only non‐real‐time applications are running with no active real‐time applications. Because a small delay in non‐real‐time traffic does not essentially impact the user's experience adversely, we deliberately allow a limited amount of delay in our proposal to attain a significant improvement in power saving. Our proposal also improves the delay in service resumption after a long period of inactivity. We use a stochastic analysis assuming an M/G/1 queue to validate this improvement.     

Direct Gravitational Search Algorithm for Global Optimisation Problems

A gravitational search algorithm (GSA) is a meta-heuristic development that is modelled on the Newtonian law of gravity and mass interaction. Here we propose a new hybrid algorithm called the Direct Gravitational Search Algorithm (DGSA), which combines a GSA that can perform a wide exploration and deep exploitation with the Nelder-Mead method, as a promising direct method capable of an intensification search. The main drawback of a meta-heuristic algorithm is slow convergence, but in our DGSA the standard GSA is run for a number of iterations before the best solution obtained is passed to the Nelder-Mead method to refine it and avoid running iterations that provide negligible further improvement. We test the DGSA on 7 benchmark integer functions and 10 benchmark minimax functions to compare the performance against 9 other algorithms, and the numerical results show the optimal or near optimal solution is obtained faster.     

Multi-objective sine-cosine algorithm (MO-SCA) for multi-objective engineering design problems

This paper proposes a novel and an effective multi-objective optimization algorithm named multi-objective sine-cosine algorithm (MO-SCA) which is based on the search technique of sine-cosine algorithm (SCA). MO-SCA employs the elitist non-dominated sorting and crowding distance approach for obtaining different non-domination levels and to preserve the diversity among the optimal set of solutions, respectively. The effectiveness of the method is measured by implementing it on multi-objective benchmark problems that have various characteristics of Pareto front such as convex, non-convex and discrete. This proposed algorithm is also checked for the multi-objective engineering design problems with distinctive features. Furthermore, we show the proposed algorithm effectively generates the Pareto front and is easy to implement and algorithmically simple.

     

Controller synthesis for dynamic hierarchical real-time plants using timed automata

We use timed I/O automata based timed games to synthesize task-level reconfiguration services for cost-effective fault tolerance in a case study. The case study shows that state-space explosion is a severe problem for timed games. By applying suitable abstractions, we dramatically improve the scalability. However, timed I/O automata do not facilitate algorithmic abstraction generation techniques. The case study motivates the development of timed process automata to improve modeling and analysis for controller synthesis of time-critical plants which can be hierarchical and dynamic. The model offers two essential features for industrial systems: (i) compositional modeling with reusable designs for different contexts, and (ii) state-space reduction technique. Timed process automata model dynamic networks of continuous-time communicating plant processes which can activate other plant processes. We show how to establish safety and reachability properties of timed process automata by reduction to solving timed games. To mitigate the state-space explosion problem, an algorithmic state-space reduction technique using compositional reasoning and aggressive abstractions is also proposed. In this article, we demonstrate the theoretical framework of timed process automata and the effectiveness of the proposed state-space reduction technique by extending the case study.