A Decentralized Replica Placement Algorithm for Edge Computing

Aral, Atakan; Ovatman, Tolga

doi:10.1109/tnsm.2017.2788945

Cited by 106 publications

(54 citation statements)

References 54 publications

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“…Di/On/Dy/nM Heuristic [13] Defines a trade-off between cost and latency. Evaluates cost of storing replicas and expected latency improvement, to make a migration or duplication decision.…”

Section: Solutions Referencesmentioning

confidence: 99%

An Overview of Service Placement Problem in Fog and Edge Computing

2020

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To support the large and various applications generated by the Internet of Things (IoT), Fog Computing was introduced to complement the Cloud Computing and offer Cloud-like services at the edge of the network with low latency and real-time responses. Large-scale, geographical distribution and heterogeneity of edge computational nodes make service placement in such infrastructure a challenging issue. Diversity of user expectations and IoT devices characteristics also complexify the deployment problem. This paper presents a survey of current research conducted on Service Placement Problem (SPP) in the Fog/Edge Computing. Based on a new classification scheme, a categorization of current proposals is given and identified issues and challenges are discussed.

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“…Di/On/Dy/nM Heuristic [13] Defines a trade-off between cost and latency. Evaluates cost of storing replicas and expected latency improvement, to make a migration or duplication decision.…”

Section: Solutions Referencesmentioning

confidence: 99%

An Overview of Service Placement Problem in Fog and Edge Computing

2020

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“…Additionally, contacting all the original nodes with a name ID corresponding to a prefix and picking the one with the best utility requires linear time and communication complexities, and is not a scalable solution. To efficiently map a virtual replica to an original node Strategy Availability-Awareness Locality-Awareness Utility-Awareness Replication on path [22,[31][32][33] Reactive ✗ ✓ Virtual nodes [34] Reactive ✗ ✓ Replication on neighbors [29,48] Reactive ✗ ✓ Randomized [35][36][37][38][39][40][41][42] Proactive ✗ ✗ Power-of-choice [56,57] Proactive ✗ ✓ Cluster-based [43,44] Proactive ✗ ✓ Correlation-based [23,45] Proactive ✗ ✓ GLARAS [13] -✓ ✗ Pyramid…”

Section: Pyramid Algorithmmentioning

confidence: 99%

“…Evaluating the data availability of a P2P storage system by the availabilityawareness of its replicas is only applicable to the homogeneous systems [23,35,[46][47][48], where nodes participate with similar bandwidths. In such systems, a larger number of online replicas reflects a higher available bandwidth, and hence a better level of data availability for the data requesters.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Utility- and Locality-Aware Replication for Heterogeneous DHT-Based P2P Cloud Storage Systems

Hassanzadeh-Nazarabadi

Küpçü

Özkasap

2020

IEEE Trans. Parallel Distrib. Syst.

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As a Distributed Hash Table (DHT), Skip Graph routing overlays are exploited in several peer-to-peer (P2P) services, including P2P cloud storage. The fully decentralized replication algorithms that are applicable to the Skip Graph-based P2P cloud storage fail on improving the performance of the system with respect to both the availability of replicas as well as their response time. Additionally, they presume the system as homogeneous with respect to the nodes' latency distribution, availability behavior, bandwidth, or storage. In this paper, we propose Pyramid , which is the first fully decentralized utility-and locality-aware replication approach for Skip Graph-based P2P cloud storage systems. Pyramid considers the nodes as heterogeneous with respect to their latency distribution, availability behavior, bandwidth, and storage. Pyramid is utility-aware as it maximizes the average available bandwidth of replicas per time slot (e.g., per hour). Additionally, Pyramid is locality-aware as it minimizes the average latency between nodes and their closest replica. Our simulation results show that compared to the state-of-the-art solutions that either perform good in utility-awareness, or in locality-awareness, our proposed Pyramid improves both the utility-and locality-awareness of replicas with a gain of about 1.2 and 1.1 times at the same time, respectively.

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“…services. An adaptive consistency approach in this environment should consider more criteria specifically replica and edge servers placement [69,70], client context-awareness [39], security and privacy [55]:…”

Section: Consistency In Emerging Computing Architecturesmentioning

confidence: 99%

A comparative analysis of adaptive consistency approaches in cloud storage

Khelaifa

Benharzallah

Kahloul

et al. 2019

Journal of Parallel and Distributed Computing

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NoSQL storage systems are used extensively by web applications and provide an attractive alternative to conventional databases due to their high security and availability with a low cost. High data availability is achieved by replicating data in different servers in order to reduce access time lag, network bandwidth consumption and system unreliability. Hence, the data consistency is a major challenge in distributed systems. In this context, strong consistency guarantees data freshness but affects directly the performance and availability of the system. In contrast, weaker consistency enhances availability and performance but increases data staleness. Therefore, an adaptive consistency strategy is needed to tune, during runtime, the consistency level depending on the criticality of the requests or data items. Although there is a rich literature on adaptive consistency approaches in cloud storage, there is a need to classify as well as regroup the approaches based on their strategies. This paper will establish a set of comparative criteria and then make a comparative analysis of existing adaptive consistency approaches. A survey of this kind not only provides the user/researcher with a comparative performance analysis of the approaches but also clarifies the suitability of these for candidate cloud systems.

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A Decentralized Replica Placement Algorithm for Edge Computing

Cited by 106 publications

References 54 publications

An Overview of Service Placement Problem in Fog and Edge Computing

An Overview of Service Placement Problem in Fog and Edge Computing

Decentralized Utility- and Locality-Aware Replication for Heterogeneous DHT-Based P2P Cloud Storage Systems

A comparative analysis of adaptive consistency approaches in cloud storage

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