Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Scalable, Data- intensive Network Computation

To enable groups of collaborating researchers at different locations to effectively share large datasets and investigate their spontaneous hypotheses on the fly, we are interested in de- veloping a distributed system that can be easily leveraged by a variety of data intensive applications. The system is composed of (i) a number of best effort logistical depots to en- able large-scale data sharing and in-network data processing, (ii) a set of end-to-end tools to effectively aggregate, manage and schedule a large number of network computations with attendant data movements, and (iii) a Distributed Hash Table (DHT) on top of the generic depot services for scalable data management. The logistical depot is extended by following the end-to-end principles and is modeled with a closed queuing network model. Its performance characteristics are studied by solving the steady state distributions of the model using local balance equations. The modeling results confirm that the wide area network is the performance bottleneck and running concurrent jobs can increase resource utilization and system throughput. As a novel contribution, techniques to effectively support resource demanding data- intensive applications using the ¯ne-grained depot services are developed. These techniques include instruction level scheduling of operations, dynamic co-scheduling of computation and replication, and adaptive workload control. Experiments in volume visualization have proved the effectiveness of these techniques. Due to the unique characteristic of data- intensive applications and our co-scheduling algorithm, a DHT is implemented on top of the basic storage and computation services. It demonstrates the potential of the Logistical Networking infrastructure to serve as a service creation platform

Simulation for Reliability, Hardware Security, and Ising Computing in VLSI Chip Design

The continued scaling of VLSI circuits has provided a wealth of opportunities andchallenges to the VLSI circuit design area. Both these challenges and opportunities, however,require new simulation tools that can enable their solution or exploitation as classicalmethods typically dealt with problem domains with smaller scales or less complexity. Inthis dissertation, simulation methods are presented to address the emerging VLSI designtopics of Electromigration induced aging and Ising computing and are then applied to theapplication areas of hardware security and graph partitioning respectively.The Electromigration aging effect in VLSI circuits is a long-term reliability issueaffecting current carrying metal wires leading to IR drop degradation. Typically, simpleanalytical equations can determine a wire’s effective age or if it will be affected by the EMaging effect at all. However, these classical methods are overly conservative and can lead toover design or unnecessary design iterations. Furthermore, it is expected that the EM agingeffect will become more severe in future Integrated Cirucits (ICs) due to increasing currentdensities and the prevalance of polycrystaline copper atom structures seen at small wiredimensions. For this reason, more comprehensive simulation techniques that can efficientlysimulate the EM effect with less conservative results can help mitigate overdesign andincrease design margins while reducing design iterations.The area of Hardware Security is becoming increasingly important as the chipsupply chain becomes more globalized and the integrity of chips becomes more diffiuclt toverify. Utilizing the accurate simulation techniques for EM, we can utilize this reliabilityeffect to demonstrate how a reliability based attack could be perpatrated. Furthermore, wecan utilize this aging effect as a defense mechanism to help us validate the integrity of anIC and detect counterfeit chips in the component supply chain market.Ising computing is an emerging method of solving combinatorial optimization problemsby simulating the interactions of so-called spin glasses and their interactions. Borrowingconcepts from quantum computing, this methods mimics the quantum interaction betweenspin glasses in such a way that finding a ground state of these spin glass models leadsto the solution of a particular problem. In this dissertation, effective methods of simulatingthe spin glass interactions using General Purpose Graphics Processing Units (GPGPUs)and finding their ground state are developed.In addition to the GPU based Ising model simulations, important combinatorialproblems can be mapped to the Ising model. In this dissertation the Ising solver is appliedto graph partitioning which can be utilized in VLSI design and many other domains as well.Specifically, solvers for the maxcut problem and the balanced min-cut partitioning problemare developed

Large-Scale Distributed Coalition Formation

The CyberCraft project is an effort to construct a large scale Distributed Multi-Agent System (DMAS) to provide autonomous Cyberspace defense and mission assurance for the DoD. It employs a small but flexible agent structure that is dynamically reconfigurable to accommodate new tasks and policies. This document describes research into developing protocols and algorithms to ensure continued mission execution in a system of one million or more agents, focusing on protocols for coalition formation and Command and Control. It begins by building large-scale routing algorithms for a Hierarchical Peer to Peer structured overlay network, called Resource-Clustered Chord (RC-Chord). RC-Chord introduces the ability to efficiently locate agents by resources that agents possess. Combined with a task model defined for CyberCraft, this technology feeds into an algorithm that constructs task coalitions in a large-scale DMAS. Experiments reveal the flexibility and effectiveness of these concepts for achieving maximum work throughput in a simulated CyberCraft environment