Analysis of energy saving in user equipment in LTE-A using stochastic modelling

Telecommunication Systems - Energy saving in User Equipment (UE) is one of the important issues for limited sources of power in the device. It is critical for the UE to maximize its energy...     

Analytical modeling of Transmission Control Protocol NewReno using Generalized Stochastic Petri Nets

This paper presents a novel analytical model of Transmission Control Protocol (TCP) using a generalized stochastic Petri net (GSPN). Extensive simulation work has been done for the performance evaluation of TCP NewReno protocol. In view of the limitations of the simulation technique, we present an analytical approach using GSPN. A GSPN is a useful mathematical tool that solves continuous time Markov chains for complex systems and evaluates the stationary behavior. In this paper, we analyze the slow‐but‐steady variant of TCP NewReno. The model captures the behavioral aspects of the slow start and the congestion avoidance phase together with the fast retransmit and recovery capabilities of TCP NewReno. Performance metrics such as throughput, goodput, and task completion time of the system are obtained. The effect of variation in the model parameters on the performance is studied. The results are validated using the network simulator, and their accuracy is verified by evaluating the confidence interval. The performance of the proposed model is compared with that of TCP Reno. The performance of the proposed model is also compared with one of the previous models. The numerical illustrations and comparison of the proposed technique with simulation validates the accuracy, efficiency, and competence of the GSPN technique. While GSPN modeling for TCP is investigated in depth for the TCP NewReno and TCP Reno variant in this paper, other protocols could be also analyzed similarly. Copyright © 2013 John Wiley & Sons, Ltd.     

Analytical modeling of bidirectional multi‐channel IEEE 802.11 MAC protocols

This paper presents an analytical approach to model the bi‐directional multi‐channel IEEE 802.11 MAC protocols (Bi‐MCMAC) for ad hoc networks. Extensive simulation work has been done for the performance evaluation of IEEE 802.11 MAC protocols. Since simulation has several limitations, this work is primarily based on the analytical approach. The objective of this paper is to show analytically the performance advantages of Bi‐MCMAC protocol over the classical IEEE 802.11 MAC protocol. The distributed coordination function (DCF) mode of medium access control (MAC) is considered in the modeling. Two different channel scheduling strategies, namely, random channel selection and fastest channel first selection strategy are also presented in the presence of multiple channels with different transmission rates. M/G/1 queue is used to model the protocols, and stochastic reward nets (SRNs) are employed as a modeling technique as it readily captures the synchronization between events in the DCF mode of access. The average system throughput, mean delay, and server utilization of each MAC protocol are evaluated using the SRN formalism. We also validate our analytical model by comparison with simulation results. The results obtained through the analytical modeling approach illustrate the performance advantages of Bi‐MCMAC protocols with the fastest channel first scheduling strategy over the classical IEEE 802.11 protocol for TCP traffic in wireless ad hoc networks. Copyright © 2010 John Wiley & Sons, Ltd.     

Performance analysis of IEEE 802.11 DCF with stochastic reward nets

In this paper, we present a performance study to evaluate the mean delay and the average system throughput of IEEE 802.11‐based wireless local area networks (WLANs). We consider the distributed co‐ordination function (DCF) mode of medium access control (MAC). Stochastic reward nets (SRNs) are used as a modelling formalism as it readily captures the synchronization between events in the DCF mode of access. We present a SRN‐based analytical model to evaluate the mean delay and the average system throughput of the IEEE 802.11 DCF by considering an on–off traffic model and taking into account the freezing of the back‐off counter due to channel capture by other stations. We also compute the mean delay suffered by a packet in the system using the SRN formulation and by modelling each station as an M/G/1 queue. We validate our analytical model by comparison with simulations. Copyright © 2006 John Wiley & Sons, Ltd.     

A Time Series Framework for Pricing Guaranteed Lifelong Withdrawal Benefit

Computational Economics - In this work, the pricing problem of a variable annuity (VA) contract embedded with a guaranteed lifelong withdrawal benefit (GLWB) rider has been considered. VAs are...     

Semi-Markov modeling of dependability of VoIP network in the presence of resource degradation and security attacks

Nowadays VoIP has become an evolutionary technology in telecommunications. Hence it is very important to study and enhance its dependability attributes. In this paper, an analytical dependability model for VoIP is proposed. The study is focused on analyzing the combined effects of resource degradation and security breaches on the Quality of Service (QoS) of VoIP, to enhance its overall dependability. As a preventive maintenance policy to prevent or postpone software failures which cause resource degradation, software rejuvenation is adopted. The dependability model is analyzed using semi-Markov process which captures the effects of non-Markovian nature of the time spent at various states of the system. The steady-state as well as the time-dependent analysis of the dependability model is presented. The steady-state results are obtained analytically, whereas the time-dependent results are obtained from simulation. Also, the analytical model is validated via simulation. The model analysis using a numerical example indicates the feasibility of our approach. Various dependability attributes such as availability, reliability and confidentiality are also obtained. A comparative study is also done between our proposed model and the existing models.     

Evolutionary multi criteria design optimization of robot grippers

This paper explores the use of intelligent techniques to obtain optimum geometrical dimensions of a robot gripper. The optimization problem considered is a non-linear, complex, multi-constraint and multicriterion one. Three robot gripper configurations are optimized. The aim is to find Pareto optimal front for a problem that has five objective functions, nine constraints and seven variables. The problem is divided into three cases. Case 1 has first two objective functions, the case 2 considers last three objective functions and case 3 deals all the five objective functions. Intelligent optimization algorithms namely Multi-objective Genetic Algorithm (MOGA), Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-objective Differential Evolution (MODE) are proposed to solve the problem. Normalized weighting objective functions method is used to select the best optimal solution from Pareto optimal front. Two multi-objective performance measures (solution spread measure (SSM) and ratio of non-dominated individuals (RNIs)) are used to evaluate the strength of the Pareto optimal fronts. Two more multi-objective performance measures namely optimizer overhead (OO) and algorithm effort are used to find the computational effort of MOGA, NSGA-II and MODE algorithms. The Pareto optimal fronts and results obtained from various techniques are compared and analyzed.     

Time integrators based on approximate discontinuous Hamiltonians

We introduce a class of time integration algorithms for finite dimensional mechanical systems whose Hamiltonians are separable. By partitioning the system's configuration space to construct an approximate potential energy, we define an approximate discontinuous Hamiltonian (ADH) whose resulting equations of motion can be solved exactly. The resulting integrators are symplectic and precisely conserve the approximate energy, which by design is always close to the exact one. We then propose two ADH algorithms for finite element discretizations of nonlinear elastic bodies. These result in two classes of explicit asynchronous time integrators that are scalable and, because they conserve the approximate Hamiltonian, could be considered to be unconditionally stable in some circumstances. In addition, these integrators can naturally incorporate frictionless contact conditions. We discuss the momentum conservation properties of the resulting methods and demonstrate their performance with several problems, such as rotating bodies and multiple collisions of bodies with rigid boundaries. Copyright © 2011 John Wiley & Sons, Ltd.     

Reducing session establishment delay using timed out packets in SIP signaling network

Session Initiation Protocol (SIP) has a retransmission mechanism to maintain the reliability for its real time transmission. But these real time transmissions cause overload in the server and creates redundant messages. SIP does not offer sufficient mechanisms for handling overload situations. In this paper, we study the SIP system behavior by separating signaling traffic in two different classes (Invites and Non‐invites) and creating a cut‐off priority queueing model. SIP retransmission mechanism with timeout is modeled as a queueing system with impatient customers. Using this model, the effect of unnecessary retransmissions is studied, and delay distribution and loss probability (Pb_loss) are calculated. The proposed analytical model is verified with simulations that demonstrate that the inclusion of timeout gives better delay performance. Using Pb_loss, an algorithm is developed to control the overload in hop‐by‐hop transaction as described in RFC 6357. The simulation results for the proposed model with overload control and the standard SIP as per RFC 3261 are compared. The results demonstrate that the server utilization factor of an overloaded server always remains less than one and hence avoids system collapse. Further, the redundant messages in the system are reduced by 30% as compared with the standard SIP network. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal portfolio trading subject to stochastic dominance constraints under second‐order autoregressive price dynamics

This paper studies the optimal portfolio trading problem under the generalized second‐order autoregressive execution price model. The problem of minimizing expected execution cost under the proposed price model is formulated as a quadratic programming (QP) problem. For a risk‐averse trader, problem formulation under the second‐order stochastic dominance constraints results in a quadratically constrained QP problem. Under some conditions on the execution price model, it is proved that the portfolio trading problems for risk‐neutral and risk‐averse traders become convex programming problems, which have many theoretical and computational advantages over the general class of optimization problems. Extensive numerical illustrations are provided, which render the practical significance of the proposed execution price model and the portfolio trading problems.