Reliability and high availability in cloud computing environments: a reference roadmap

Abstract

Reliability and high availability have always been a major concern in distributed systems. Providing highly available and reliable services in cloud computing is essential for maintaining customer confidence and satisfaction and preventing revenue losses. Although various solutions have been proposed for cloud availability and reliability, but there are no comprehensive studies that completely cover all different aspects in the problem. This paper presented a ‘Reference Roadmap’ of reliability and high availability in cloud computing environments. A big picture was proposed which was divided into four steps specifying through four pivotal questions starting with ‘Where?’, ‘Which?’, ‘When?’ and ‘How?’ keywords. The desirable result of having a highly available and reliable cloud system could be gained by answering these questions. Each step of this reference roadmap proposed a specific concern of a special portion of the issue. Two main research gaps were proposed by this reference roadmap.

An energy efficient service composition mechanism using a hybrid meta-heuristic algorithm in a mobile cloud environment

“…To evaluate the fitness value, the main objective of the proposed algorithm is selecting a composited service with a minimized fitness value. According to Table 2, the existing QoS factors are calculated with sum and product operations [33] and are normalized between (0, 1). Table 2.…”

Task scheduling mechanisms in cloud computing: A systematic review

“…Since we know that task scheduling is an NP‐hard problem, we need certain algorithms for this allocation. There are various optimization algorithms which schedule the tasks optimally on the cloud . Task scheduling allocates a set of workflows to a number of appropriate processors in such a way that execution and communication costs are minimized.…”

“…There are various optimization algorithms which schedule the tasks optimally on the cloud. 15 Task scheduling allocates a set of workflows to a number of appropriate processors in such a way that execution and communication costs are minimized. The allocation of processors to a set of tasks is called a mapping.…”

Dependability analysis for characterizing Google cluster reliability

“…Due to the distributed systems inherent complexity, the large-scale cloud computing services are prone to various runtime faults caused by different hardware or software computing resource failures. [15][16][17][18][19] The large-scale heterogeneity nature of cloud services leads to frequent failures in these systems. Cloud computing data centers offer thousands of physical servers networked via high bandwidth network infrastructures that communicate with one another to provide highly available and flexible services.…”

“…2 Although cloud computing services suggest many benefits, there are also many issues and open research problems to provide these services such as load balancing solutions, [3][4][5][6][7] security challenges, [8][9][10][11] task scheduling, [12][13][14] and high availability/reliability challenges. [15][16][17][18][19] The large-scale heterogeneity nature of cloud services leads to frequent failures in these systems. 20 Physical server failures cause the runtime failure for executing jobs on these servers.…”