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Top1. Introduction
Cloud is budding as an influential technology, which initiates various services such as resource virtualization, utility computing and software as a service. It indulges the foundation of cloud computing that provides reasonable and realistic access to computing facilities for the open public. The gratified cloud services may involve multi-domain resources and multi-provider in cooperation with integration to legacy services and infrastructures. The inter-cloud domains, models and tools provide an interoperable environment for more complex and enterprise oriented services (Denchenko, 2013).
The data oriented cloud services inspire several database structures for various data functioning and utilities. Nowadays, many social networking sites, shopping websites, forecast agencies, MNCs etc. deals with a huge amount of data. (Agrawal, 2014) The data are not attaining importance just for quantity rather adoring cloud computing functionalities as one may retrieve a lot of information from it. Users must be careful with the thought what and when to retrieve, as they need to have confidence on timeliness and accuracy over the data being processed. (SAS, 2013) (Peluso, 2012) This helps in deriving the data which must maintain a balance between various attributes such as determining reliability, validation, debugging, auditing, also the quality of data evaluation (Agrawal, 2014; Rapolu, 2013).
The data can be of different kind whether it is micro data or big data, where not just the storage and capacity, but the improvised computational and statistical methods are tracking research over such data marking a boon in the IT industry (Rolli, 2011). Today, petabytes and zettabytes of data cascaded into organizations also initiates various challenges mainly understanding data, addressing data quality, maintaining velocity, dealing with outliers, displaying significant results, etc. (Grov, 2014; Hong, et al., 2013; Padhye & Tripathi, 2015).
Transactional distributed systems concur with two general approaches data distribution and replication to address scalability and availability requirements (Cai, 2011). Network communication over the cloud experiences concurrency, fault tolerance and performance issues that might be resolved by incorporating scalable properties like network partitioning, caching, and automatic failure detection. (Rapolu, 2013) Furthermore an effective coordination is supposed to be set up between owners and users also the developers and system operators, to maintain inter-cloud and intra-cloud communication (Rapolu, 2013).
Thus, paper is divided into several sections that contribute in the following way:
- 1.
Firstly, we provide a Version based architecture for cloud assisted communication network. Where the section 1 expresses introduction flow of challenges faced by transactional database version updates followed by how data is handled in the clustered environment and the related works proposed by various authors is described (see sections 2-4);
- 2.
Secondly, a service management bus is introduced to handle middleware cluster environment which reduces communication overheads. Thus, the projected work model and goals are explained through progressive algorithm and process flow (see sections 5-7);
- 3.
Thirdly, VIP layer is proposed in the network which is responsible to maintain version update identification and verification. In addition, evaluation of layer and architecture is expressed resulting into precisely calculated response graph with an initial implementation setup archetype scenario (see sections 8-10).