AbstractWith the rapid development of Cloud computing technologies and wideadopt of Cloud services and applications, QoS provisioning in Clouds be-comes an important research topic. In this paper, we propose an admis-sion control mechanism for Cloud computing. In particular we considerthe high volume of simultaneous requests for Cloud services and developadmission control for aggregated trac ows to address this challenge. Byemploy network calculus, we determine e ective bandwidth for aggregateow, which is used for making admission control decision. In order toimprove network resource allocation while achieving Cloud service QoS,we investigate the relationship between e ective bandwidth and equiva-lent capacity. We have also conducted extensive experiments to evaluateperformance of the proposed admission control mechanism. 1 Introduction Recently the emerging Cloud computing has been developing very quickly[1, 2, 3]. With the rapid development of Cloud computing technologies and wideadoption of Cloud-based applications, the huge amount of trac generated bya large number of users for accessing Cloud services bring in a series challengeto the Internet. The best-e ort service model in the current Internet cannotmeet users’ requirements for Quality of Service (QoS). Call Admission Control(CAC) o ers an e ective approach to controlling network trac and avoiding1
ACM Sigcomm 2006 published a paper [26] which was perceived to unify the deterministic and stochastic branches of the network calculus (abbreviated throughout as DNC and SNC) [39]. Unfortunately, this seemingly fundamental unification---which has raised the hope of a straightforward transfer of all results from DNC to SNC---is invalid. To substantiate this claim, we demonstrate that for the class of stationary and ergodic processes, which is prevalent in traffic modelling, the probabilistic arrival model from [26] is quasi-deterministic, i.e., the underlying probabilities are either zero or one. Thus, the probabilistic framework from [26] is unable to account for statistical multiplexing gain, which is in fact the raison d'etre of packet-switched networks. Other previous formulations of SNC can capture statistical multiplexing gain, yet require additional assumptions [12], [22] or are more involved [14], [9] [28], and do not allow for a straightforward transfer of results from DNC. So, in essence, there is no free lunch in this endeavor. Our intention in this paper is to go beyond presenting a negative result by providing a comprehensive perspective on network calculus. To that end, we attempt to illustrate the fundamental concepts and features of network calculus in a systematic way, and also to rigorously clarify some key facts as well as misconceptions. We touch in particular on the relationship between linear systems, classical queueing theory, and network calculus, and on the lingering issue of tightness of network calculus bounds. We give a rigorous result illustrating that the statistical multiplexing gain scales as Ω(√N), as long as some small violations of system performance constraints are tolerable. This demonstrates that the network calculus can capture actual system behavior tightly when applied carefully. Thus, we positively conclude that it still holds promise as a valuable systematic methodology for the performance analysis of computer and communication systems, though the unification of DNC and SNC remains an open, yet quite elusive task.  We present an admission control scheme for real-time VBR traffic. The deterministic guarantee on the end-to-end delay bound is adopted as the measure of quality-of-service (QoS). The network environment of our admission control algorithm is the connection-oriented network, in which every network node uses the rate-controlled service (RCS) discipline based on the earliest deadline first (EDF) scheduling policy. Unlike the previous studies, this paper focuses on designing an efficient bandwidth allocation scheme, in which the service curve and the spare capacity curve are two important terminologies employed. Experiments using the parameters derived from some real video traces show that our algorithm performs better than previous ones in terms of both the network bandwidth utilization and the computational time needed. From the Publisher: Providing performance guarantees is one of the most important issues for future telecommunication networks. This book describes theoretical developments in performance guarantees for telecommunication networks from the last decade. Written for the benefit of graduate students and scientists interested in telecommunications-network performance this book consists of two parts. This paper addresses the problem of computing end-to-end delay bounds for a traffic flow traversing a tandem of FIFO multiplexing network nodes using Network Calculus. Numerical solution methods are required, as closed-form delay bound expressions are unknown except for few specific cases. For the methodology called the Least Upper Delay Bound, the most accurate among those based on Network Calculus, exact and approximate solution algorithms are presented, and their accuracy and computation cost are discussed. The algorithms are inherently exponential, yet affordable for tandems of up to few tens of nodes, and amenable to online execution in cases of practical significance. This complexity is, however, required to compute accurate bounds. As the LUDB may actually be larger than the worst-case delay, we assess how close the former is to the latter by computing lower bounds on the worst-case delay and measuring the gap between the lower and upper bound.    A calculus is developed for obtaining bounds on delay and buffering requirements in a communication network operating in a packet switched mode under a fixed routing strategy. The theory developed is different from traditional approaches to analyzing delay because the model used to describe the entry of data into the network is nonprobabilistic. It is supposed that the data stream entered into the network by any given user satisfies burstiness constraints. A data stream is said to satisfy a burstiness constraint if the quantity of data from the stream contained in any interval of time is less than a value that depends on the length of the interval. Several network elements are defined that can be used as building blocks to model a wide variety of communication networks. Each type of network element is analyzed by assuming that the traffic entering it satisfies bursting constraints. Under this assumption, bounds are obtained on delay and buffering requirements for the network element; burstiness constraints satisfied by the traffic that exits the element are derived. > Worst-case bounds on delay and backlog are derived for leaky bucket constrained sessions in arbitrary topology networks of generalized processor sharing (GPS) servers. The inherent flexibility of the service discipline is exploited to analyze broad classes of networks. When only a subset of the sessions are leaky bucket constrained, we give succinct per-session bounds that are independent of the behavior of the other sessions and also of the network topology. However, these bounds are only shown to hold for each session that is guaranteed a backlog clearing rate that exceeds the token arrival rate of its leaky bucket. A much broader class of networks, called consistent relative session treatment (CRST) networks is analyzed for the case in which all of the sessions are leaky bucket constrained. First, an algorithm is presented that characterizes the internal traffic in terms of average rate and burstiness, and it is shown that all CRST networks are stable. Next, a method is presented that yields bounds on session delay and backlog given this internal traffic characterization. The links of a route are treated collectively, yielding tighter bounds than those that result from adding the worst-case delays (backlogs) at each of the links in the route. The bounds on delay and backlog for each session are efficiently computed from a universal service curve, and it is shown that these bounds are achieved by "staggered" greedy regimes when an independent sessions relaxation holds. Propagation delay is also incorporated into the model. Finally, the analysis of arbitrary topology GPS networks is related to Packet GPS networks (PGPS). The PGPS scheme was first proposed by Demers, Shenker and Keshav (1991) under the name of weighted fair queueing. For small packet sizes, the behavior of the two schemes is seen to be virtually identical, and the effectiveness of PGPS in guaranteeing worst-case session delay is demonstrated under certain assignments. >   