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The development of context-aware applications in ubiquitous environments depends not only on the user interactions but also on several context parameters. The handling of these parameters is a fundamental problem in these systems. The key purpose of this work is to enrich the unified modeling language (UML) class diagram with new constructs to provide a universal model capable of coping with the context-awareness concerns.

The authors provide a review of existing context handling approaches. Afterward, they relied on the UML extensibility mechanisms to propose a heavyweight extension for the UML class diagram. This generic approach allows describing the different context parameters since the modeling phase.

Existing solutions for context handling apply the contextual constraints on finished applications or tend to be dependent on a specific development process. This paper presents a solution based on UML, which allows dealing with context since the modeling phase, and independently of development processes. This proposal is implemented as an eclipse editor and illustrated through a case study in the healthcare field.

This paper addresses the problem of context handling, and it presents a review of the foremost existing solutions. The paper also presents a heavyweight extension for the UML class diagram, which consists in enriching it with additional constructs, capable of monitoring how applications are linked to context parameters and how the values of these parameters may affect the application behavior.

Scalability is a fundamental problem in mobile ad hoc networks (MANETs), where network topology includes large number of nodes and demands a large number of packets in network that characterized by dynamic topologies, existence of bandwidth constrained, variable capacity links, energy constraint and nodes are highly prone to security threats. The key purpose of this paper is to overview the efficiency of the proposed clustering scheme for large-scale MANETs and its performance evaluation and especially in the case of a large number of nodes in the network.

Designing clustering schemes for MANETs, which are efficient and scalable in the case of large number of mobile nodes, has received a great attention in the last few years. It is widely used to improve resources management, hierarchical routing protocol design, quality of service, network performance parameters such as routing delay, bandwidth consumption, throughput and security. MANETs are characterized by limited wireless bandwidth, nodes mobility that results in a high frequency of failure regarding wireless links, energy constraint and nodes are highly prone to security threats. Due to all these features, the design of a scalable and efficient clustering scheme is quite complex. Many clustering schemes have been proposed to divide nodes into clusters, focusing on different metrics and purposes.

To the best of the author's knowledge, the different proposed clustering schemes are not scalable when the network size increases to a very large number. The paper presents the clustering scheme in detail and its performance evaluation by simulating MANETs composed of a large number of mobile nodes. The authors compare the performance of the scheme with a number of existing clustering schemes such as lowest-ID, highest degree, and weighted clustering algorithm, based on a number of performance metrics. Simulation results show that the scheme performs better than other clustering schemes, based on the performance metrics considered, for large-scale MANETs.

This paper addresses the problem of scalability in MANETs when there are high numbers of node in the network. The paper analyses the performance of the proposed clustering scheme for large-scale MANETs. The obtained results show that the different proposed clustering schemes do not allow the scalability when the network size is very large. The scheme supports scalability efficiently when the number of nodes increases in the network (more than 2,000 nodes).