424 research outputs found
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
Enhanced Forwarding Strategies in Information Centric Networking
Content Centric Networking (CCN), a Clean Slate architecture to Information Centric Networking (ICN) , uses new approaches to routing named content, achieving scalability, security and performance. This thesis proposes a design of an effective multi-path forwarding strategy and performs an evaluation of this strategy in a set of scenarios that consider large scale deployments. The evaluations show improved performance in terms of user application throughput, delays, adoptability and scalability against adverse conditions (such as differing background loads and mobility) compared to the originally proposed forwarding strategies. Secondly, this thesis proposes an analytical model based on Markov Modulated Rate Process (MMRP) to characterize multi-path data transfers in CCN. The results show a close resemblance in performance between the analytical model and the simulation model
A Review on Cache Replacement Strategies in Named Data Network
Named Data Network (NDN) architecture is one of the newest and future-aspired Internet communication systems. Video-on-Demand (VoD) has rapidly emerged as a popular online service. However, it is costly, considering its high bandwidth and popularity. Internet on-demand video traffic has been growing quite fast, and on-demand video streaming has gained much attention. The problem of this study is that the NDN architecture is processing several forms of online video requests simultaneously. However, limited cache and multiple buffering of requested videos result in loss of data packet as a consequence of the congestion in the cache storage network. Addressing this problem is essential as congestion cause network instability. This work emphasizes on the review of cache replacement strategies to deal with the congestion issue in Named Data Networks (NDN) during the VoD delivery in order to determine the performance (strengths and weaknesses) of the cache replacement strategies. Finally, this study proposes the replacement strategies must be enhanced with a new strategy that depends on popularity and priority regarding the congestion. This study would positively benefits both suppliers and users of Internet videos
The ZCache: Decoupling Ways and Associativity
Abstract—The ever-increasing importance of main memory latency and bandwidth is pushing CMPs towards caches with higher capacity and associativity. Associativity is typically im-proved by increasing the number of ways. This reduces conflict misses, but increases hit latency and energy, placing a stringent trade-off on cache design. We present the zcache, a cache design that allows much higher associativity than the number of physical ways (e.g. a 64-associative cache with 4 ways). The zcache draws on previous research on skew-associative caches and cuckoo hashing. Hits, the common case, require a single lookup, incurring the latency and energy costs of a cache with a very low number of ways. On a miss, additional tag lookups happen off the critical path, yielding an arbitrarily large number of replacement candidates for the incoming block. Unlike conventional designs, the zcache provides associativity by increasing the number of replacement candidates, but not the number of cache ways. To understand the implications of this approach, we develop a general analysis framework that allows to compare associativity across different cache designs (e.g. a set-associative cache and a zcache) by representing associativity as a probability distribution. We use this framework to show that for zcaches, associativity depends only on the number of replacement candidates, and is independent of other factors (such as the number of cache ways or the workload). We also show that, for the same number of replacement candidates, the associativity of a zcache is superior than that of a set-associative cache for most workloads. Finally, we perform detailed simulations of multithreaded and multiprogrammed workloads on a large-scale CMP with zcache as the last-level cache. We show that zcaches provide higher performance and better energy efficiency than conventional caches without incurring the overheads of designs with a large number of ways. I
Gain More for Less: The Surprising Benefits of QoS Management in Constrained NDN Networks
Quality of Service (QoS) in the IP world mainly manages forwarding resources,
i.e., link capacities and buffer spaces. In addition, Information Centric
Networking (ICN) offers resource dimensions such as in-network caches and
forwarding state. In constrained wireless networks, these resources are scarce
with a potentially high impact due to lossy radio transmission. In this paper,
we explore the two basic service qualities (i) prompt and (ii) reliable traffic
forwarding for the case of NDN. The resources we take into account are
forwarding and queuing priorities, as well as the utilization of caches and of
forwarding state space. We treat QoS resources not only in isolation, but
correlate their use on local nodes and between network members. Network-wide
coordination is based on simple, predefined QoS code points. Our findings
indicate that coordinated QoS management in ICN is more than the sum of its
parts and exceeds the impact QoS can have in the IP world
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