Single Service Class Research Articles

A holistic approach to a context-aware IoT ecosystem with Adaptive Ubiquitous Middleware

The Internet of Things is envisioned to provide connectivity and communication between various devices all over the world. Based on the devices and applications involved, the nature of the network formed differs. Thus, an intelligent and holistic ecosystem needs to be created wherein clients, data sources, smart objects, and services can all co-exist and interact with each other. We present Adaptive Ubiquitous Middleware for context-aware IoT ecosystems, which considers the situational context of the applications, devices, or people and the contexts of the network formed and accordingly adapts the behavior of the ecosystem. Adaptive Ubiquitous Middleware is a multi-agent, multi-communication protocol-facilitated middleware that acts as an integration point for applications to access relevant context, share it with other applications, and have relevant services made available via a multi-communication protocol bridge. We also present an optimal service allocation model for a single service class that utilizes available computing resources and achieves a minimum average response time. The system implementation has been evaluated with two use cases to demonstrate its applicability, effectiveness, and generality. The evaluation of optimal service allocation demonstrates the service response is much faster in the proposed model.

Differentiation service of level in multiservice call centers with adaptation servers

In this article study large-scale service systems with several classes of customers. The following question of the necessary number of servers and compliance with the requirements of customers to reduce the cost of personnel in conditions of limiting the quality of service at the class level is considered. The characteristics of the planning and staffing scheme that are asymptotically optimal under constrained conditions are made, since the load on the system increases to infinity. Asymptotic modes are considered in accordance with the quality and efficiency of management, the quality of management and the effectiveness of management within a single class of service.

Evaluation of the Impact of EDoS Attacks Against Cloud Computing Services

Cloud computing is currently one of the fastest growing segments of IT. To date, and according to a recent survey conducted by the International Data Corporation, security is the biggest challenge to cloud computing. A cloud introduces resource-rich computing platforms, where adopters are charged based on the usage of the cloud’s resources, known as “pay-as-you-use” or utility computing. However, a conventional Distributed Denial-of-Service (DDoS) attack on server and network resources compromises cloud computing services by charging cloud adopters more cost due to the attack activities that consume cloud’s resources. In such case, the main goal of such attack is to make the cloud computing unsustainable by targeting the cloud adopter’s economic resources. Thus, it constitutes a new breed of DDoS attacks, namely Economic Denial of Sustainability (EDoS) attack. In this paper, we study the impact of EDoS attacks on the cloud computing services, considering only a single class of service. We developed an analytical model verified by a simulation model to study such impact of EDoS attacks on the cloud computing. The analytical model relies on the queuing model that captures the cloud services and considers a number of performance and cost metrics including end-to-end response time, utilization of computing resources, throughput, and the incurred cost resulting from the attack.

Call Admission Control and Handoff Techniques for 3-G and Beyond Mobile Networks

Cellular mobile communication Networks have many services and each type of Services has distinct characteristics and Quality of Service requirement. It is important issues in 3-G and beyond networks are to prepare a framework for multiple class service, which performs call admission and handoff efficiently. There have been handful existing mechanisms for improving Call Admission Control (CAC) and Handoff Techniques in mobile network but most of them have considered only single class of service or might have touched value of few classes but not beyond. In this paper we have considered 8 types of services, which are differentiated according to their: Acceptable delay in transmission, Buffering capacity, Transmission mode and Bit rate. In this approach CAC and Handoff issues are resolved by awarding calls with some Priority Number by which each call will be recognized. Another issue of collision in CAC and handoff will be resolved by priority and authority to access the channel. Performance of this frame- work for CAC and Handoff is evaluated by calculating Call Dropping probability and Call Completion probability in this paper.

Internet QoS and Regulations

This paper investigates Internet service provider (ISP) incentives with a single-service class and with two-service classes in the Internet. We consider multiple competing ISPs who offer network access to a fixed user base, consisting of end-users who differ in their quality requirements and willingness to pay for the access. We model user-ISP interactions as a game in which each ISP makes capacity and pricing decisions to maximize its profits and the end-users only decide which service to buy (if any) and from which ISP. Our model provides pricing for networks with single- and two-service classes for any number of competing ISPs. Our results indicate that multiple service classes are socially desirable, but could be blocked due to the unfavorable distributional consequences that it inflicts on the existing Internet users. We propose a simple regulatory tool to alleviate the political economic constraints and thus make multiple service classes in the Internet feasible.

Optical Packet Contention Resolution Through Edge Smoothing Into Decomposed Subflows

Motivated by the difficulty of implementing optical packet switches having large optical buffers, we propose a new, simple, and effective way of applying electronic traffic smoothing at the edge of an optical packet switched network to reduce core optical buffering requirements. A single class of service is assumed. Incoming traffic that is destined for a particular egress edge router is smoothed at each ingress edge router by a buffer scheduling algorithm and decomposed into several constant bit rate subflows, each with a uniform packet interarrival time. Each such subflow emerging from a core switch also retains these traffic characteristics. The rates of these subflows obey a simple mathematical relationship, and it is shown that, with the appropriate queuing strategy, this substantially reduces the core buffering requirements. Indeed, it is shown through analysis and simulation that scalability is improved over existing approaches, and computation is simplified. The proposal in this paper requires much less core buffering than one without smoothing, while compared with other smoothing proposals, it is more scalable both to large networks and a large number of smoothed flows. A condition on the fiber delay line buffer depth requirements is also derived for no packet loss to take place in any of the scenarios modeled in this paper. Furthermore, it is confirmed through simulation that packet jitter is not generated in the network core.

Probabilistic call admission control in wireless multiservice networks

A new probabilistic call admission control scheme is proposed for multiservice wireless networks. The new scheme gradually suppresses the admission rate of the new calls and of the calls of each service class (SC) supported considering their priorities independently. The scheme is examined both for a single SC and for multiple SCs under general conditions. The analysis employs Markov chain theory and yields analytical expressions for the call blocking probabilities. The proposed analytical method was validated via simulations employing different distributions for the channel holding time; the simulations demonstrated the accuracy of the proposed framework.

Connection provisioning with guaranteed recovery time in survivable WDM optical networks

Optical networks employing wavelength- division multiplexing (WDM) are prone to failures. In case of a failure, the time to recovery is an important metric, since the amount of lost information and the performance of carried application strongly depends on the time of service interruption. Moreover, as the current trend in network development is moving toward a unified solution providing support for voice, data and various multimedia services, different application and users may tolerate different time of service interruption. Therefore, it is imperative to provide recovery-time guaranteed connections in WDM optical networks. In this paper, we propose a new shared-segment protection algorithm, called AGBSP-QoP, to provision connection requests according to their differentiated recovery-time requirements. Given a working path, AGBSP-QoP first computes all possible recovery-time guaranteed working-backup segment pairs, and then dynamically selects a least-cost eligible subset based on a dexterously constructed auxiliary graph. We conduct simulations under single class of service and multiple classes of service, and compare AGBSP-QoP with other protection algorithms. The results show that AGBSP-QoP yields the best performance and can properly provision connection requests according to their differentiated recovery-time requirements.

Modular neural networks for multi-service connection admission control

Although neural networks (NNs) have been applied for traffic and congestion control in ATM networks, many implementations only consider a single service class with identical traffic characteristics and requirements. In addition, the most commonly used NN is the multi-layer perceptron (MLP) networks which are known to converge slowly. We present a multi-service connection admission control (CAC) scheme that harness the fast learning capability of modular neural networks for cell-loss-ratio (CLR) prediction at each switch. The proposed scheme does not require precise models of network processes and detailed knowledge of higher-order moments of the traffic. Simulations were carried out to compare the performance of the proposed scheme with an equivalent bandwidth (EBW) method.

Traffic management and QoS provisioning in future wireless IP networks

The huge commercial success of mobile telephony, phenomenal growth of mobile and Internet users, and emerging popularity of IP-based multimedia applications are the major driving forces behind third-generation (3G) evolution. 3G will bring will bring applications, both data and multimedia, into wireless environments. It will operate on IP-based infrastructures to provide wider service access capability. However, current IP is designed for data applications with a single service class, best-effort. Therefore, it is insufficient to support real-time applications that require diverse quality of service (QoS). Although IP can provide greater service flexibility in terms of spectrum efficiency and QoS, it is not the most appropriate choice in wireless environments. In order to support real-time applications in wireless IP networks, measurement-based admission control (MBAC) is considered. We consider two admission criteria, reservation and priority. The system performance is measured in terms of new call blocking and hand-off call dropping probabilities with three different levels of user mobility: low, moderate and high level of mobility. Considering the delay-tolerant nature of real-time applications in wireless IP networks, the effect of delay tolerance on the overall system performance is also investigated. We discuss the suitability of MBAC in wireless IP networks by comparing its pros and cons with traditional parameter based schemes, and then describe its procedures. Next, we discuss simulation details, and present simulation results with discussions. We compare new and hand-off traffic performance with strictly policy-based and policy and traffic characteristic-based admission control schemes. We discuss the effectiveness of MBAC and its role in 3G and forthcoming 4G networks.

Internet service classes under competition

This paper analyzes competition between two Internet service providers (ISPs), either or both of which may choose to offer multiple service classes. In the model analyzed, a social planner who maximizes the total benefit from network usage and a profit maximizing monopolist will both form multiple service classes; but two networks competing to maximize profits will not. The reason is that a competition effect always outweighs a segmentation effect. Networks wish to offer multiple service classes in order to increase user benefits and hence charge higher prices. In doing so, however, they effectively increase the number of points in the service quality range at which they compete. Consequently, in any equilibrium competitive outcome, both ISPs offer a single service class. The analysis has particular implications for the Paris Metro pricing (PMP) proposal, which is considered in depth in this paper, since it suggests that PMP may not be viable under competition.

Multiperiod Airline Overbooking with a Single Fare Class

Consider a multiperiod airline overbooking problem that relates to a single-leg flight and a single service class. Passengers may cancel their reservations at any time, including being no-shows at flight-time. At that time, the airline bumps passengers in excess of flight capacity and pays a penalty for so doing. We give conditions on the fares, refunds, and distributions of passenger demand for reservations and cancellations in each period, and on the bumping penalty function, that ensure that a booking-limit policy is optimal, i.e., in each period the airline accepts reservation requests up to a booking limit if the number of initial reservations is less than that booking limit, and declines reservation requests otherwise. The optimal booking limits are easily computed. We give conditions under which the optimal booking limits are monotone in the time to flight departure. The model is applied to the discount allocation problem in which lower fare classes book prior to higher fare classes.

Optimal control of continuous-time terminal-value birth-and-death processes and airline overbooking

Consider a continuous-time airline overbooking problem that relates to a single-leg flight and a single service class with a stationary fare. Passengers may cancel their reservations at any time and receive a full refund. Therefore fares can be thought of as being paid at flight time. At that time, the airline bumps passengers in excess of flight capacity and pays a penalty for so doing. The wflight-time revenue, that is, fares received less bumping penalties paid, is quasiconcave in the number of reservations at that time. We model the reservations process as a continuous-time terminal-value birth-and-death process. A more general model than is necessary for an airline reservations system is considered, in which the airline controls both the reservation acceptance (birth) and the cancellation (death) rates. In current practice airlines do not control cancellation rates (though other industries do exercise such control, e.g., hotels) and control reservation acceptance rates by declining reservation requests. The more general model might be applied to other targeting applications, such as steering a vehicle through space toward a target location. For the general model a piecewise-constant booking-limit policy is optimal; that is, at all times the airline accepts reservation requests up to a booking limit if the current number of reservations is less than that booking limit, and declines reservation requests otherwise. When the airline is allowed to decline all reservation requests, as is the case in practice, the booking-limit optimal policy defined by using the greatest optimal booking limit at all times is piecewise constant. Moreover, these booking limits fall toward flight time. © 1996 John Wiley & Sons, Inc.

Approximate mean value analysis of client-server systems with multi-class requests

Stochastic Rendezvous Networks (SRVNs) are performance models for multitasking parallel software with intertask communication via rendezvous introduced in [1], which are very appropriate to model client-server systems. SRVNs differ from Queueing Networks (QNs) in two ways: nodes act as both clients and servers (allowing for nested service), and servers have two distinct phases of service—the first one “in RV” with the client, and the second “after RV”, executed in parallel with the client. Early work on solving SRVN models has used a kind of approximate Mean Value Analysis based on heuristic ad hoc assumptions to determine the task queue properties at the instant of RV request arrivals. Approximation are necessary since SRVN violates product form. Recently, a more rigorous approach was proposed in [2] for the solution of SRVN models, based on a special aggregation (named “Task-Directed Aggregation” TDA) of the Markov chain model describing the interference of different clients that contend for a single server with FIFO queueing discipline and different service times. The algorithm derived in [2] has the limitation that each client may require only a single class of service. In general, a software server offers a range of services with different workloads and functionalities, and a client may need more than one service. The present paper uses the TDA approach to derive an extended algorithm which allows a client to require any number of services from a server by changing randomly the request class. The new algorithm is incorporated into a decomposition method for models with any number of servers. The SRVN modelling technique is applied to a large case study of a distributed database system, giving insight into the behaviour of the system and helping to identify performance problems such as software bottle-neck.