Different Classes Of Requests Research Articles

Adaptive Carrier Aggregation with Differentiating Cloud Services for Maximizing Radio Resource Efficiency and Reward Toward 5G Cellular Network

Toward 5G cellular network, to achieve an extremely high data rate and Ultra Reliable Low Latency Communication by using a limited radio frequency spectrum bands becomes a big challenge. 3GPP LTE-A/LTE-A Pro thus specifies the technologies of Carrier Aggregation (CA) and Network Function Virtualization (NFV) to increase the frequency spectrum efficiency and to dynamically allocate the virtualized network component for different classes of requests, respectively. CA can aggregate multiple contiguous or non-contiguous Component Carriers (CCs) and to improve frequency spectrum utilization and signal quality. NFV can dynamically allocate network (virtualized) resource for different classes of services, e.g., human-driven Cloud Computing, machine-driven Internet of Vehicles (IoVs) (e.g., Autonomous Self Driving Vehicle) and sensing-based Internet of Things (IoTs), etc. However, different SINRs of different frequency spectrum bands suffer from the exiting radio nature of CCs. The CA effect and system capacity are thus limited obviously. Additionally, in CC accesses via IoV/IoT, human-driven and machine-driven types communications exhibit different arrival requests and traffic characteristics. Various QoS requirements and traffic distributions of Human and Machine transmissions are certainly different. This paper thus proposes the Cross-Layer scheduling with CC Aggregation (CLCA) toward 5G. CLCA consists of three mechanisms: (1) Markov Decision Process-based cost reward Packet Selection (MDP-PS), (2) Adaptive Packet Scheduling (APS) and (3) Adaptive Component Carrier scheduling (ACC). Numerical results demonstrate that the proposed CLCA approach outperform the compared approaches in system capacity, network reward and packet failure rate.

Evaluation of memory capacity for heavily loaded systems with priorities

Subject of Research. The paper deals with the models of computer networks represented by queuing systems with heterogeneous flow of requests. The models show processing and transmission of packets of different classes. Requirements for the quality indicators of packet transmission for each class are implemented by the use of the priority service disciplines. Operation in high load conditions is a distinctive feature of modern telecommunication systems, leading to probability increase of packets (requests) loss. This necessitates the use of models with limited memory capacity. Analytic study of such models is accompanied by complex and bulky mathematical calculations with explicit results only in special cases under certain assumptions. For example, with regard to the probability laws, describing the processes of receiving and serving of requests that limits the usage of such models. Method. The study of such systems with simulation methods is also problematic in view of statistical instability of operation characteristics for high load conditions. We propose an approach to the study of heavily loaded systems with priorities based on the models with unlimited memory capacity. Main Results. Analytical results for service characteristics with two moments of distribution were obtained. The distribution laws approximation of the number of requests in system is based on these results. Practical Relevance. We have shown the possibility of approximation of continuous multi-exponential distributions that enable to assess memory capacity for given probability of losses for different classes of requests.

Analysis of loss networks with routing

This paper analyzes stochastic networks consisting of finite capacity nodes with different classes of requests which move according to some routing policy. The Markov processes describing these networks do not have, in general, reversibility properties so that the explicit expression of their invariant distribution is not known. A heavy traffic limit regime is considered: the arrival rates of calls as well as the capacities of the nodes are proportional to a factor going to infinity. It is proved that, in the limit, the associated rescaled Markov process converges to a deterministic dynamical system with a unique equilibrium point characterized by a non-standard fixed point equation.

Disk scheduling in a multimedia I/O system

This article provides a retrospective of our original paper by the same title in the Proceedings of the First ACM Conference on Multimedia, published in 1993. This article examines the problem of disk scheduling in a multimedia I/O system. In a multimedia server, the disk requests may have constant data rate requirements and need guaranteed service. We propose a new scheduling algorithm, SCAN-EDF, that combines the features of SCAN type of seek optimizing algorithm with an Earliest Deadline First (EDF) type of real-time scheduling algorithm. We compare SCAN-EDF with other scheduling strategies and show that SCAN-EDF combines the best features of both SCAN and EDF. We also investigate the impact of buffer space on the maximum number of video streams that can be supported.We show that by making the deadlines larger than the request periods, a larger number of streams can be supported.We also describe how we extended the SCAN-EDF algorithm in the PRISM multimedia architecture. PRISM is an integrated multimedia server, designed to satisfy the QOS requirements of multiple classes of requests. Our experience in implementing the extended SCAN-EDF algorithm in a generic operating system is discussed and performance metrics and results are presented to illustrate how the SCAN-EDF extensions and implementation strategies have succeeded in meeting the QOS requirements of different classes of requests.

Cluster reserves

In network (e.g., Web) servers, it is often desirable to isolate the performance of different classes of requests from each other. That is, one seeks to achieve that a certain minimal proportion of server resources are available for a class of requests, independent of the load imposed by other requests. Recent work demonstrates how to achieve this performance isolation in servers consisting of a single, centralized node; however, achieving performance isolation in a distributed, cluster based server remains a problem. This paper introduces a new abstraction, the cluster reserve, which represents a resource principal in a cluster based network server. We present a design and evaluate a prototype implementation that extends existing techniques for performance isolation on a single node server to cluster based servers. In our design, the dynamic cluster-wide resource management problem is formulated as a constrained optimization problem, with the resource allocations on individual machines as independent variables, and the desired cluster-wide resource allocations as constraints. Periodically collected resource usages serve as further inputs to the problem. Experimental results show that cluster reserves are effective in providing performance isolation in cluster based servers. We demonstrate that, in a number of different scenarios, cluster reserves are effective in ensuring performance isolation while enabling high utilization of the server resources.