IEEE Software Defined Network Initiative

This paper outlines a proposal for setting up an IEEE initiative on software defined networks (SDNs) to facilitate professional and academic exchange of SDN-related ideas, research, and development. The proposal is a result of an intensive effort of a team consisting of the authors. After a comprehensive gap analysis, gaps and key opportunities were identified. Finally, a specific set of components along with schedule and financial consideration were proposed in the areas of publications, conferences, standards, education, certification, and publicity

Towards 5G Software-Defined Ecosystems: Technical Challenges, Business Sustainability and Policy Issues

Techno-economic drivers are creating the conditions for a radical change of paradigm in the design and operation of future telecommunications infrastructures. In fact, SDN, NFV, Cloud and Edge-Fog Computing are converging together into a single systemic transformation termed “Softwarization” that will find concrete exploitations in 5G systems. The IEEE SDN Initiative1 has elaborated a vision, an evolutionary path and some techno-economic scenarios of this transformation: specifically, the major technical challenges, business sustainability and policy issues have been investigated. This white paper presents: 1) an overview on the main techno-economic drivers steering the “Softwarization” of telecommunications; 2) an introduction to the Open Mobile Edge Cloud vision (covered in a companion white paper); 3) the main technical challenges in terms of operations, security and policy; 4) an analysis of the potential role of open source software; 5) some use case proposals for proof-of-concepts; and 6) a short description of the main socio-economic impacts being produced by “Softwarization”. Along these directions, IEEE SDN is also developing of an open catalogue of software platforms, toolkits, and functionalities aiming at a step-by-step development and aggregation of test-beds/field-trials on SDNNFV- 5G

Software-Defined Networks for Future Networks and Services: Main Technical Challenges and Business Implications

In 2013, the IEEE Future Directions Committee (FDC) formed an SDN work group to explore the amount of interest in forming an IEEE Software-Defined Network (SDN) Community. To this end, a Workshop on "SDN for Future Networks and Services" (SDN4FNS'13) was organized in Trento, Italy (Nov. 11th-13th 2013). Following the results of the workshop, in this paper, we have further analyzed scenarios, prior-art, state of standardization, and further discussed the main technical challenges and socio-economic aspects of SDN and virtualization in future networks and services. A number of research and development directions have been identified in this white paper, along with a comprehensive analysis of the technical feasibility and business availability of those fundamental technologies. A radical industry transition towards the "economy of information through softwarization" is expected in the near future

Dynamic control of a single-server system with abandonments

In this paper, we discuss the dynamic server control in a two-class service system with abandonments. Two models are considered. In the first case, rewards are received upon service completion, and there are no abandonment costs (other than the lost opportunity to gain rewards). In the second, holding costs per customer per unit time are accrued, and each abandonment involves a fixed cost. Both cases are considered under the discounted or average reward/cost criterion. These are extensions of the classic scheduling question (without abandonments) where it is well known that simple priority rules hold. The contributions in this paper are twofold. First, we show that the classic c-μ rule does not hold in general. An added condition on the ordering of the abandonment rates is sufficient to recover the priority rule. Counterexamples show that this condition is not necessary, but when it is violated, significant loss can occur. In the reward case, we show that the decision involves an intuitive tradeoff between getting more rewards and avoiding idling. Secondly, we note that traditional solution techniques are not directly applicable. Since customers may leave in between services, an interchange argument cannot be applied. Since the abandonment rates are unbounded we cannot apply uniformization-and thus cannot use the usual discrete-time Markov decision process techniques. After formulating the problem as a continuous-time Markov decision process (CTMDP), we use sample path arguments in the reward case and a savvy use of truncation in the holding cost case to yield the results. As far as we know, this is the first time that either have been used in conjunction with the CTMDP to show structure in a queueing control problem. The insights made in each model are supported by a detailed numerical study. © 2010 Springer Science+Business Media, LLC

Server Allocation in Grid Systems with On/Off Sources

Abstract. A system consisting of a number of servers, where demands of different types arrive in bursts (modelled by interrupted Poisson processes), is examined in the steady state. The problem is to decide how many servers to allocate to each job type, so as to minimize a cost function expressed in terms of average queue sizes. First, an exact analysis is provided for an isolated IP/M/n queue. The results are used to compute the optimal static server allocation policy. The latter is then compared to two heuristic policies which employ dynamic switching of servers from one queue to another (such switches take time and hence incur costs).

Optimal Server Allocation in Reconfigurable Clusters with Multiple Job Types

We examine a system where the servers in a cluster may be switched dynamically and preemptively from one kind of work to another. The demand consists of M jobs..

Resource capacity allocation to stochastic dynamic competitors:knapsack problem for perishable items and index-knapsack heuristic

In this paper we propose an approach for solving problems of optimal resource capacity allocation to a collection of stochastic dynamic competitors. In particular, we introduce the knapsack problem for perishable items, which concerns the optimal dynamic allocation of a limited knapsack to a collection of perishable or non-perishable items. We formulate the problem in the framework of Markov decision processes, we relax and decompose it, and we design a novel index-knapsack heuristic which generalizes the index rule and it is optimal in some specific instances. Such a heuristic bridges the gap between static/deterministic optimization and dynamic/stochastic optimization by stressing the connection between the classic knapsack problem and dynamic resource allocation. The performance of the proposed heuristic is evaluated in a systematic computational study, showing an exceptional near-optimality and a significant superiority over the index rule and over the benchmark earlier-deadline-first policy. Finally we extend our results to several related revenue management problems