Weighted Scheduling of Time-Sensitive Coflows

Datacenter networks commonly facilitate the transmission of data in distributed computing frameworks through coflows, which are collections of parallel flows associated with a common task. Most of the existing research has concentrated on scheduling coflows to minimize the time required for their completion, i.e., to optimize the average dispatch rate of coflows in the network fabric. Nevertheless, modern applications often produce coflows that are specifically intended for online services and mission-crucial computational tasks, necessitating adherence to specific deadlines for their completion. In this paper, we introduce \wdcoflow,~ a new algorithm to maximize the weighted number of coflows that complete before their deadline. By combining a dynamic programming algorithm along with parallel inequalities, our heuristic solution performs at once coflow admission control and coflow prioritization, imposing a $\sigma$-order on the set of coflows. With extensive simulation, we demonstrate the effectiveness of our algorithm in improving up to $3\times$ more coflows that meet their deadline in comparison the best SoA solution, namely $\mathtt{CS\text{-}MHA}$. Furthermore, when weights are used to differentiate coflow classes, \wdcoflow~ is able to improve the admission per class up to $4\times$, while increasing the average weighted coflow admission rate.Comment: Submitted to IEEE Transactions on Cloud Computing. Parts of this work have been presented at IFIP Networking 202

MMB & DFT 2014 : Proceedings of the International Workshops ; Modeling, Analysis and Management of Social Networks and their Applications (SOCNET 2014) & Demand Modeling and Quantitative Analysis of Future Generation Energy Networks and Energy-Efficient Systems (FGENET 2014)

At present, a comprehensive set of measurement, modeling, analysis, simulation, and performance evaluation techniques are employed to investigate complex networks. A direct transfer of the developed engineering methodologies to related analysis and design tasks in next-generation energy networks, energy-efficient systems and social networks is enabled by a common mathematical foundation. The International Workshop on "Demand Modeling and Quantitative Analysis of Future Generation Energy Networks and Energy-Efficient Systems" (FGENET 2014) and the International Workshop on "Modeling, Analysis and Management of Social Networks and their Applications" (SOCNET 2014) were held on March 19, 2014, at University of Bamberg in Germany as satellite symposia of the 17th International GI/ITG Conference on "Measurement, Modelling and Evaluation of Computing Systems" and "Dependability and Fault-Tolerance" (MMB & DFT 2014). They dealt with current research issues in next-generation energy networks, smart grid communication architectures, energy-efficient systems, social networks and social media. The Proceedings of MMB & DFT 2014 International Workshops summarizes the contributions of 3 invited talks and 13 reviewed papers and intends to stimulate the readers’ future research in these vital areas of modern information societies.Gegenwärtig wird eine reichhaltige Klasse von Verfahren zur Messung, Modellierung, Analyse, Simulation und Leistungsbewertung komplexer Netze eingesetzt. Die unmittelbare Übertragung entwickelter Ingenieurmethoden auf verwandte Analyse- und Entwurfsaufgaben in Energienetzen der nächsten Generation, energieeffizienten Systemen und sozialen Netzwerken wird durch eine gemeinsame mathematische Basis ermöglicht. Die Internationalen Workshops "Demand Modeling and Quantitative Analysis of Future Generation Energy Net-works and Energy-Efficient Systems" (FGENET 2014) und "Modeling, Analysis and Management of Social Networks and their Applications" (SOCNET 2014) wurden am 19. März 2014 als angegliederte Symposien der 17. Internationalen GI/ITG Konferenz "Measurement, Modelling and Evaluation of Computing Systems" und "Dependability and Fault-Tolerance" (MMB & DFT 2014) an der Otto-Friedrich-Universität Bamberg in Deutschland veranstaltet. Es wurden aktuelle Forschungsfragen in Energienetzen der nächsten Generation, Smart Grid Kommunikationsarchitekturen, energieeffizienten Systemen, sozialen Netzwerken und sozialen Medien diskutiert. Der Tagungsband der Internationalen Workshops MMB & DFT 2014 fasst die Inhalte von 3 eingeladenen Vorträgen und 13 begutachteten Beiträgen zusammen und beabsichtigt, den Lesern Anregungen für ihre eigenen Forschungen auf diesen lebenswichtigen Gebieten moderner Informationsgesellschaften zu vermitteln

A Routing Protocol and Energy Efficient Techniques in Bluetooth Scatternets

In this paper, we propose a protocol for routing in Bluetooth scatternets. The protocol uses the available battery power in the Bluetooth (BT) devices as a cost metric in choosing the routes. We evaluate the throughput performance as a function of packet arrival rate and number of piconets. A throughput of about 120 Kbps/piconet is shown to be achieved in a 5piconet scatternet. We propose two techniques, namely a) battery power level based master-slave switch and b) distance based power control, to increase the network lifetime in scatternets. The master-slave switch technique is motivated by the fact that a piconet master has to handle the packet transmissions to/from all its slaves, and hence may drain its battery soon. We propose a role switching idea where each BT device in a piconet may have to play the master role depending on its available battery power. In the second technique, we propose that the BT devices choose their transmit powers based on their distances from their respective masters. Our performance results show that a considerable gain in network lifetime can be achieved using these two power saving techniques

Asymptotics of insensitive load balancing and blocking phases

Abstract We study a single class of traf?c acting on a symmetric set of processorsharing queues with ?nite buffers, and we consider the case where the load scales with the number of servers. We address the problem of giving robust performance bounds based on the study of the asymptotic behaviour of the insensitive load balancing schemes, which have the desirable property that the stationary distribution of the resulting stochastic network depends on the distribution of job-sizes only through its mean.Itwasshownforsmallsystemswithlossesthattheygivegoodestimatesofperformanceindicators,generalizinghenceforthErlangformula,whereasoptimalpolicies are already theoretically and computationally out of reach for networks of moderate size. We characterize the response of symmetric systems under those schemes at different scales and show that three amplitudes of deviations can be identi?ed according towhether?1.Acentrallimitscalingtakesplaceforasub-critical load; for ? =1, the number of free servers scales like n ? ?+1 (? being the buffer depth and n being the number of servers) and is of order 1 for super-critical loads. This further implies the existence of different phases for the blocking probability. Before a (re?ned) critical load ?c(n) = 1 ? an? ? ?+1, the blocking is exponentially small and becomes of order n? ? ?+1 at ?c(n). This generalizes the well-known quality-and

Performance of Code Allocation Algorithms on UMTS Uplink with Mixed Voice/Data Traffic

In this paper we are concerned with the performance evaluation of code allocation algorithms in Universal Mobile Telecommunication System (UMTS) networks. UMTS networks will offer multiple services (voice, data, video, etc.) with different quality-of-service (QoS) requirements to mobile users. We evaluate the performance of different code (rate) allocation algorithms on the UMTS uplink in a mixed voice/data traffic scenario. Two different code allocation algorithms are considered, one based on the overall buffer occupancy at the user terminal, and the other based on dividing the available codes equally among the requesting users. Further, for a data-only system, we evaluate the performance of two algorithms for rate and power allocation based on received signal-to-interference ratio (SIR) at the base station

Performance Analysis of Battery Power Management Schemes in Wireless Mobile Devices

In this paper, we analyze the performance of battery power management schemes in wireless mobile devices using a queueing theory approach. We model the battery as a server with finite service capacity and data packets as customers to be served. With an intent to exploit the recharging capability of the battery when left idle, we allow the battery to go on intentional vacations during which the battery can recharge itself. The recharge thus built up can effectively increase the number of customers served (in other words, battery life can be extended). Such improved battery life performance would, however, come at the expense of increased packet delay performance. We quantify the battery life gain versus delay performance trade-off in this approach through analysis and simulations. By considering a continuous recharge model of the battery, we derive expressions for the number of customers served and the mean delay for an M=GI=1 queueing system without and with server vacations. We show that allowing intentional vacations during busy periods helps to increase battery life, and that this approach can be beneficial when applied on traffic of delay-tolerant applications. We also propose a packet delay constrained power saving algorithm that will exploit the recharge phenomenon when packet delay constraints are imposed. I

Is the Price of Anarchy the Right Measure for Load-Balancing Games?

International audiencePrice of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. For a non-cooperative load-balancing game with two classes of servers and for a finite or infinite number of dispatchers, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic