In wireless sensor networks (WSNs), long lifetime requirement of different applications and limited energy storage capability of sensor nodes has led us to find out new horizons for reducing power consumption upon nodes. To increase sensor node's lifetime, circuit and protocols have to be energy efficient so that they can make a priori reactions by estimating and predicting energy consumption. The goal of this study is to present and discuss several strategies such as power-aware protocols, cross-layer optimization, and harvesting technologies used to alleviate power consumption constraint in WSNs.

In order to explore the most current information and react faster to changing business conditions, organizations consider real‐time data warehousing a powerful technique to achieve operational business intelligence (BI). We propose in this paper a novel real‐time data warehouse (RTDW) framework based on the virtualization concept. Our approach introduces a conceptual modelling technique, known as ring modelling, for real‐time data management and multidimensional analysis. This technique produces a flexible semi‐structured data model that accommodates unknown business process data and relationships as they evolve, handles schema changes and aggregate‐management efficiently, and scales well with the large size of increasing data volumes. With the help of a telecommunication business example, We evaluated our proposed approach in an extensive experimental study where we compared our approach Ring Model with existing structured multidimensional conceptual models (MCMs), i.e. relational OLAP and multidimensional OLAP, and with semi‐structured MCM, i.e. XML Cubes, in terms of scalability, data storage estimations, data updates loading time, and query response times. Our performance results show that encouraging speedups are achieved.

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Identifying a multicast label-switched-path (LSP) tree that satisfy a set of traffic-oriented and resource-oriented QoS constraints such as cost, reliability, bandwidth, jitter, and delay, has become an important research issue in the area of multicast routing in MPLS networks. In general, multiconstrained multicast tree-selection is an NP-complete problem. In this survey, QoS-based multicast tree-selection algorithms from the perspective of optimization techniques are evaluated. The existing algorithms are classified into three dimensions: non-MPLS-/MPLS-based, single/multiple QoS constrained, and heuristic-/unicast-/artificial-intelligence optimization techniques. In addition to state-of-the-art review of existing solutions, this article highlights important characteristics of QoS-based MPLS multicast algorithms and discuss important issues that are worthy of investigation in future research activities.