Jgroup/ARM: a distributed object group platform with autonomous replication management

Meling, Hein; Montresor, Alberto; Helvik, Bjarne E.; Babaoğlu, Özalp

doi:10.1002/spe.853

Cited by 25 publications

(43 citation statements)

References 30 publications

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“…The protocols presented in subsequent sections may be implemented inside a group communication system (GCS) (e.g., Isis [16,17], Transis [8], JGroup [47], Spread [7], JGroups [13],...). Given a GCS, three different events can be distinguished with regard to message transmission, as shown in Fig.…”

Section: Reliable Causal Multicastmentioning

confidence: 99%

Scalability approaches for causal multicast: a survey

et al. 2015

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Many distributed services need to be scalable: internet search, electronic commerce, e-government... In order to achieve scalability those applications rely on replicated components. Because of the dynamics of growth and volatility of customer markets, applications need to be hosted by adaptive systems. In particular, the scalability of the reliable multicast mechanisms used for supporting the consistency of replicas is of crucial importance. Reliable multicast may propagate updates in a pre-defined order (e.g., FIFO, total or causal). Since total order needs more communication rounds than causal order, the latter appears to be the preferable candidate for achieving multicast scalability, although the consistency guarantees based on causal order are weaker than those of total order. This paper provides a historical survey of different scalability approaches for reliable causal multicast protocols.

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Section: Reliable Causal Multicastmentioning

confidence: 99%

Scalability approaches for causal multicast: a survey

et al. 2015

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“…active replication, load-sharing, etc. based on mechanisms implemented in a generic platform, e.g., [1], [14].…”

Section: A Failure Sources In the Vepcmentioning

confidence: 99%

Service Availability in the NFV Virtualized Evolved Packet Core

Gonzalez

Grønsund

Mahmood

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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Abstract-Network Function Virtualization (NFV) promises to transform the way telecom providers design and operate networks and network services. Virtualized Evolved Packet Core vEPC is one of the Network Function Virtualization NFV use cases that has got most of attention, where dependability is a major concern. In the traditional EPC, functions are deployed in proprietary network elements with proven characteristics, e.g., a defined availability, and corresponding guarantees. Hence, network operators have a firm basis for the design of a robust mobile core network. On the other hand, in the vEPC, network operators face a more challenging environment, where functions, subsystems and requirements are interrelated in a more complex manner. Hence, the assessment of the robustness of the network, and the design to meet dependability requirements becomes hard. In order to address this challenge, we provide initial guidelines and modeling tools to assess system availability in vEPC scenarios, and identify the most relevant factors to be considered in this process.

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“…In addition, a replication management infrastructure, e.g. [11,10,9], is necessary to support deployment of replicas and managing reconfigurations when failures occur. One example is the distributed autonomous replication management framework (DARM) [9].…”

Section: Introductionmentioning

confidence: 99%

Foraging for Better Deployment of Replicated Service Components

Csorba

Meling

Heegaard

et al. 2009

Distributed Applications and Interoperable Systems

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Abstract. Our work focuses on distributed software services and their requirements in terms of system performance and dependability. We target the problem of finding optimal deployment mappings involving multiple services, i.e. mapping service components in the software architecture to the underlying platforms for best possible execution. We capture important non-functional requirements of distributed services, regarding performance and dependability. These models are then used to construct appropriate cost functions that will guide our heuristic optimization method to provide better deployment mappings for service components. This paper mainly focuses on dependability. In particular, a logic enabling replication management and deployment for increased dependability is presented. To demonstrate the feasibility of our approach, we model a scenario with 15 services each with different redundancy levels deployed over a 10-node network. We show by simulation how the deployment logic proposed is capable to satisfy replica deployment requirements.

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Jgroup/ARM: a distributed object group platform with autonomous replication management

Cited by 25 publications

References 30 publications

Scalability approaches for causal multicast: a survey

Scalability approaches for causal multicast: a survey

Service Availability in the NFV Virtualized Evolved Packet Core

Foraging for Better Deployment of Replicated Service Components

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