Resource Management in Multi-Access Edge Computing (MEC)

This PhD thesis investigates the effective ways of managing the resources of a Multi-Access Edge Computing Platform (MEC) in 5th Generation Mobile Communication (5G) networks. The main characteristics of MEC include distributed nature, proximity to users, and high availability. Based on these key features, solutions have been proposed for effective resource management. In this research, two aspects of resource management in MEC have been addressed. They are the computational resource and the caching resource which corresponds to the services provided by the MEC. MEC is a new 5G enabling technology proposed to reduce latency by bringing cloud computing capability closer to end-user Internet of Things (IoT) and mobile devices. MEC would support latency-critical user applications such as driverless cars and e-health. These applications will depend on resources and services provided by the MEC. However, MEC has limited computational and storage resources compared to the cloud. Therefore, it is important to ensure a reliable MEC network communication during resource provisioning by eradicating the chances of deadlock. Deadlock may occur due to a huge number of devices contending for a limited amount of resources if adequate measures are not put in place. It is crucial to eradicate deadlock while scheduling and provisioning resources on MEC to achieve a highly reliable and readily available system to support latency-critical applications. In this research, a deadlock avoidance resource provisioning algorithm has been proposed for industrial IoT devices using MEC platforms to ensure higher reliability of network interactions. The proposed scheme incorporates Banker’s resource-request algorithm using Software Defined Networking (SDN) to reduce communication overhead. Simulation and experimental results have shown that system deadlock can be prevented by applying the proposed algorithm which ultimately leads to a more reliable network interaction between mobile stations and MEC platforms. Additionally, this research explores the use of MEC as a caching platform as it is proclaimed as a key technology for reducing service processing delays in 5G networks. Caching on MEC decreases service latency and improve data content access by allowing direct content delivery through the edge without fetching data from the remote server. Caching on MEC is also deemed as an effective approach that guarantees more reachability due to proximity to endusers. In this regard, a novel hybrid content caching algorithm has been proposed for MEC platforms to increase their caching efficiency. The proposed algorithm is a unification of a modified Belady’s algorithm and a distributed cooperative caching algorithm to improve data access while reducing latency. A polynomial fit algorithm with Lagrange interpolation is employed to predict future request references for Belady’s algorithm. Experimental results show that the proposed algorithm obtains 4% more cache hits due to its selective caching approach when compared with case study algorithms. Results also show that the use of a cooperative algorithm can improve the total cache hits up to 80%. Furthermore, this thesis has also explored another predictive caching scheme to further improve caching efficiency. The motivation was to investigate another predictive caching approach as an improvement to the formal. A Predictive Collaborative Replacement (PCR) caching framework has been proposed as a result which consists of three schemes. Each of the schemes addresses a particular problem. The proactive predictive scheme has been proposed to address the problem of continuous change in cache popularity trends. The collaborative scheme addresses the problem of cache redundancy in the collaborative space. Finally, the replacement scheme is a solution to evict cold cache blocks and increase hit ratio. Simulation experiment has shown that the replacement scheme achieves 3% more cache hits than existing replacement algorithms such as Least Recently Used, Multi Queue and Frequency-based replacement. PCR algorithm has been tested using a real dataset (MovieLens20M dataset) and compared with an existing contemporary predictive algorithm. Results show that PCR performs better with a 25% increase in hit ratio and a 10% CPU utilization overhead

Towards Practical Graph-Based Verification for an Object-Oriented Concurrency Model

To harness the power of multi-core and distributed platforms, and to make the development of concurrent software more accessible to software engineers, different object-oriented concurrency models such as SCOOP have been proposed. Despite the practical importance of analysing SCOOP programs, there are currently no general verification approaches that operate directly on program code without additional annotations. One reason for this is the multitude of partially conflicting semantic formalisations for SCOOP (either in theory or by-implementation). Here, we propose a simple graph transformation system (GTS) based run-time semantics for SCOOP that grasps the most common features of all known semantics of the language. This run-time model is implemented in the state-of-the-art GTS tool GROOVE, which allows us to simulate, analyse, and verify a subset of SCOOP programs with respect to deadlocks and other behavioural properties. Besides proposing the first approach to verify SCOOP programs by automatic translation to GTS, we also highlight our experiences of applying GTS (and especially GROOVE) for specifying semantics in the form of a run-time model, which should be transferable to GTS models for other concurrent languages and libraries.Comment: In Proceedings GaM 2015, arXiv:1504.0244

Analysis of current and future trends in synchronization, deadlock, and recovery in distributed databases

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Attributes of fault-tolerant distributed file systems

Fault tolerance in distributed file systems will be investigated by analyzing recovery techniques and concepts implemented within the following models of distributed systems: pool-processor model and user-server model. The research presented provides an overview of fault tolerance characteristics and mechanisms within current implementations and summarizes future directions for fault tolerant distributed file systems

A comparative study of concurrency control algorithms for distributed databases

The declining cost of computer hardware and the increasing data processing needs of geographically dispersed organizations have led to substantial interest in distributed data management. These characteristics have led to reconsider the design of centralized databases. Distributed databases have appeared as a result of those considerations. A number of advantages result from having duplicate copies of data in a distributed databases. Some of these advantages are: increased data accesibility, more responsive data access, higher reliability, and load sharing. These and other benefits must be balanced against the additional cost and complexity introduced in doing so. This thesis considers the problem of concurrency control of multiple copy databases. Several synchronization techniques are mentioned and a few algorithms for concurrency control are evaluated and compared

C-MOS array design techniques: SUMC multiprocessor system study

The current capabilities of LSI techniques for speed and reliability, plus the possibilities of assembling large configurations of LSI logic and storage elements, have demanded the study of multiprocessors and multiprocessing techniques, problems, and potentialities. Evaluated are three previous systems studies for a space ultrareliable modular computer multiprocessing system, and a new multiprocessing system is proposed that is flexibly configured with up to four central processors, four 1/0 processors, and 16 main memory units, plus auxiliary memory and peripheral devices. This multiprocessor system features a multilevel interrupt, qualified S/360 compatibility for ground-based generation of programs, virtual memory management of a storage hierarchy through 1/0 processors, and multiport access to multiple and shared memory units

New Fault Tolerant Multicast Routing Techniques to Enhance Distributed-Memory Systems Performance

Distributed-memory systems are a key to achieve high performance computing and the most favorable architectures used in advanced research problems. Mesh connected multicomputer are one of the most popular architectures that have been implemented in many distributed-memory systems. These systems must support communication operations efficiently to achieve good performance. The wormhole switching technique has been widely used in design of distributed-memory systems in which the packet is divided into small flits. Also, the multicast communication has been widely used in distributed-memory systems which is one source node sends the same message to several destination nodes. Fault tolerance refers to the ability of the system to operate correctly in the presence of faults. Development of fault tolerant multicast routing algorithms in 2D mesh networks is an important issue. This dissertation presents, new fault tolerant multicast routing algorithms for distributed-memory systems performance using wormhole routed 2D mesh. These algorithms are described for fault tolerant routing in 2D mesh networks, but it can also be extended to other topologies. These algorithms are a combination of a unicast-based multicast algorithm and tree-based multicast algorithms. These algorithms works effectively for the most commonly encountered faults in mesh networks, f-rings, f-chains and concave fault regions. It is shown that the proposed routing algorithms are effective even in the presence of a large number of fault regions and large size of fault region. These algorithms are proved to be deadlock-free. Also, the problem of fault regions overlap is solved. Four essential performance metrics in mesh networks will be considered and calculated; also these algorithms are a limited-global-information-based multicasting which is a compromise of local-information-based approach and global-information-based approach. Data mining is used to validate the results and to enlarge the sample. The proposed new multicast routing techniques are used to enhance the performance of distributed-memory systems. Simulation results are presented to demonstrate the efficiency of the proposed algorithms