A survey and performance evaluation of decentralized aggregation schemes for autonomic management

Abstract

SUMMARYOver the last few years, autonomic network and service management has emerged as a serious alternative to traditional management approaches. In these systems, distributed entities, called autonomic managers, perform monitoring and control operations in an autonomous and decentralized way. The monitoring consists of providing indicators on the state of the system. Several monitoring solutions have been proposed to enable autonomic managers to obtain a partial or complete knowledge of an indicator through aggregation processes. Such a profusion of solutions raises important questions regarding the choice of an aggregation scheme in a particular operational context and for a particular management information because each class of solution presents different benefits and weaknesses. That is why, in this paper, we present the result of our study of decentralized aggregation schemes for autonomic network and service monitoring. The contribution is twofold: (i) a survey of decentralized aggregation schemes based on a refined taxonomy; and (ii) the results of an evaluation campaign we performed to compare typical aggregation schemes. These results highlight the context, in terms of the managed network behaviour as well as information dynamics, in which each aggregation scheme outperforms the others, thus helping autonomic management system designers in choosing the best scheme for their management purpose.

A Game-Theoretic Approach for Elastic Distributed Data Stream Processing

“…-Tree-based protocols [Makhloufi et al 2014;Prieto and Stadler 2007] use spanning trees to collect aggregate information. The computation is performed hierarchically in a bottom-up fashion.…”

DAGGTAX: A Taxonomy of Data Aggregation Processes

“…The taxonomies proposed by Madden et al [5] and Gray et al [2] can only be applied to describe the aggregate functions of HAT, which are also captured by our taxonomy. The taxonomies of Solis et al [7], Makhloufi et al [6], and Rajagopalan [15], do not support modeling of data properties. Although Fasolo et al [4] have considered data representations, aggregate functions and aggregation protocols, their taxonomy is defined at a much coarser level and does not allow for the analysis on such detailed data and process behaviors as the aforementioned bottleneck.…”

“…Besides a classification of aggregate functions that we have discussed in the previous paragraph, Fasolo et al [4] classify the existing routing protocols according to the aggregation method, resilience to link failures, overhead to setup/maintain aggregation structure, scalability, resilience to node mobility, energy saving method and timing strategy. The aggregation protocols are also classified by Solis et al [7], Makhloufi et al [6], and Rajagopalan [15], with respect to different classification criteria. In contrast to the above works focusing mainly on aggregation protocols, Alzaid et al [8] have proposed a taxonomy of secure aggregation schemes that classifies them into different models.…”

“…Since data aggregation plays a key role in many applications, considerable research efforts have been dedicated to this topic. A number of taxonomies have been proposed to provide a comprehensive understanding on various aspects of data aggregation, such as aggregate functions ( [1], [2], [5]), aggregation protocols ( [4], [6], [7]) and security models ( [8]). …”

A New Enhanced Version of Vleach Protocol Using a Smart Path Selection

“…Consequently, the network energy consumption is reduced and its lifetime is extended. Unlike the basic end-to-end routing, DC routing family [4] [5] permits establishing paths from multiple sources toward a single destination . Some Data centric protocols are as follows:…”