In literature, combinatorial optimization problems have been solved using several hybrid strategies. From the principles of software engineering, it is explicit that modelling enables better understanding of the problem’s solution as well as the various parts that constitute the solution. However, the literature reveals that there is less importance attached to modelling the problem’s solution while solving combinatorial optimization problems using hybrid strategies. Therefore, in order to better understand the advantages and significance of using a model based approach in solving such problems, a survey on model based approach and the various properties achieved by modelling has been carried out. A comparison of the algorithm or technique based approach, framework based approach and model based approach is done to better understand the differences between the approaches and their outcomes. From the comparison made between the approaches and the analysis made on the advantages of using a model based approach in solving combinatorial optimization problems using hybrid strategies, it is found that a model based approach gives clear and better understanding of complex problems by making their representation easily modular, understandable, adaptable, verifiable, reliable, customizable, reusable etc. Further, when hybrid strategies are used, and the problems solution is depicted in the form of a model, every part of the model could be implemented using different algorithms and frameworks, thus aiding to identify the optimal algorithm or framework for every part of the model, as well as the most efficient hybrid combination that solves the whole problem in an optimal manner.

Students like to find better engineering college for their higher education. It is very challenging to find the better engineering college with conflicting criteria. In this research, the criterion such as academic reputation and achievements, infrastructure, fees structure, location, quality of the faculty, research facilities and other criterion are considered to find the better engineering college. Multi Criteria Decision Making (MCDM) is the most well known branch of decision making under the presence of conflicting criteria. TOPSIS is one of the MCDM technique widely applied to solve the problems which involves many number of criteria. In this research, TOPSIS is Adaptive and applied to find better engineering college. To evaluate the proposed methodology the parameters such as time complexity, space complexity, sensitivity analysis and rank reversal are considered. In this comparative analysis, better results are obtained for Adaptive TOPSIS compared to COPRAS.

Multi Criteria Decision Making (MCDM) methods are useful for evaluating several complex factors of multiple selection problems. The Multi-Objective problems are an extension of Single-Objective problems. The goal of MCDM is to help the decision maker to make a choice among a finite number of alternatives or to sort or rank a finite set of alternatives in terms of multiple criteria. Among the MCDM methods, the most widely applied method is TOPSIS. It is applied for different kinds of MCDM problems. In laptop selection process, it is difficult to select better laptop because relatively all laptops are seems to be same. By applying the TOPSIS method to the alternatives it is simple to differentiate the laptops from one another. The better laptop has been selected using TOPSIS based on conflicting criteria such as warranty, size, battery life, specification and others. This methodology also has been evaluated by MCDM evaluation metrics such as Time and Space Complexity, Sensitivity Analysis, ranking reversal and relative closeness coefficient. 

Composition of services provides value added service by combining existing services and is essential to meet the varying users’ requests. The need for on-demand, automated, on-the fly and failure resilient service composition led to various dynamic and adaptive service composition approaches. An overview of several existing composition approaches is provided and the limitations in these approaches are identified and depicted as research opportunities. It has been found that all these approaches behave in a rigid way to respond to the changing services environment. They are bridged by proposing a Goal-Directed Orchestration approach which employs an orchestration engine to provide flexibility in responding to the changes in dynamic services environment. To illustrate how our approach could work better than the other existing approaches, we discussed with a usage scenario in travel trip planning domain. Our proposed model is compared with the existing models based on a set of defined features.

Nowadays, Recent developments shows that, Cloud computing is a milestone in delivering IT services based on the Internet. Storage as a Service is a type of business model which rents storage space for smaller companies or even for individuals. The vendors are targeting secondary storage by promoting this service which allows a convenient way of managing backups instead of maintaining a large tape library. The key advantage of using Storage service is cost savings of hardware and physical storage spaces. In securing Storage as a Service model, there is a need for a middleware to monitor the data transmission among cloud storage and various clients. The objective of the system aims at developing a smart and integrated dynamic secured storage model which acts as a middleware in supporting all the primary security goals such as confidentiality, data integrity, and accountability. This proposed model will provide secured data dynamics, access controls and auditability. The secured data dynamics is done by Boneh Franklin-Identity Based Cryptography. This model enhances the accounting model in adding indexing policies and provides security in the audit logs through password based cryptography along with AES. This is a generic middleware assisting the basic security features for any cloud environment, so that it can be equipped for any type of system. The main advantage of the proposed system is to reduce the time complexity in encryption and decryption process and also to provide higher degree of security. We also leveraged the implementation of this middleware in a mail server environment with drive option which poses file storage and enables file sharing among the drive users.

Smart home is a relatively new technology, where we applied pervasive computing in all the aspects, so as to make our jobs or things that we normally do in-side the home in a very easier way. Originally, a smart home technology was used to control environmental systems such as lighting and heating; but recently the use of smart technology has been developed so that almost any electrical component within the home can be included in the system. Usually in pervasive computing, a middleware is developed to provide interaction between the user and device. In previous, a middleware is only suitable for specific Smart Home architecture, that can’t be applicable to any other architecture but the Generic Ubiquitous Middleware is suitable for different Smart Home architecture. This paper proposes that any smart home can be built with single architecture and it is verified using a Coloured Petri Nets tool. We have given a verification model of various Smart home Environments.

A Smart Home is an emerging technology, where the electronic devices are controlled automatically based on the occupants activities. The pervasive computing plays a vital role in the smart home environment, which provides the computer-based service to human beings anywhere and anytime. However, when discussing smart home of the future, related studies have focused on providing middleware. The middleware acts as a interface between human beings and the smart devices. In this paper, we have proposed a generic middleware model for smart home that enables interaction between human being and devices and also between various devices based on the context identified in the environment.

Business agility remains to be the keyword that drives the business into different directions and enabling a 360 degree shift in the business process. To achieve agility the organization should work on real time information and data. The need to have instant access to information appears to be ever shine requirement of all organizations or enterprise. Access to information does not come directly with a single query but a complex process termed Information integration. Information integration has been in existence for the past two decades and has been progressive up to now. The challenges and issues keep on persisting as information integration problem evolves by itself. This paper addresses the issues in the approaches, techniques and models pertaining to information integration and identifies the problem for a need for a complete model. As SOA is the architectural style that is changing the business patterns today, this paper proposes a service oriented model for information integration. The model mainly focuses on giving a complete structure for information integration that is adaptable to any environment and open in nature. Here information is converted into service and then the information services are integrated through service oriented integration to provide the integrated information also as service.

Pervasive computing aims at developing smart environments which enable user to interact with other devices. Pervasive computing includes a middleware to support interoperability, heterogeneity and self-management among different platforms. It provides efficient communications and context awareness among devices. Middleware for pervasive computing provides much more attention to coordinate the devices in the smart environment. The evaluation of the pervasive middleware is a challenging endeavor. The scope of evaluating smart environment is mainly increasing due to various devices involved in that environment. In this paper evaluation metrics are proposed based on the contexts available in the environment, how the devices are used, security and autonomy of smart applications. These metrics are used for evaluating different kind of smart applications.

Qualitative bankruptcy prediction rules represent experts' problem-solving knowledge to predict qualitative bankruptcy. The objective of this research is predicting qualitative bankruptcy using ant-miner algorithm. Qualitative data are subjective and more difficult to measure. This approach uses qualitative risk factors which include fourteen internal risk factors and sixty eight external risk factors associated with it. By using these factors qualitative prediction rules are generated using ant-miner algorithm and the influence of these factors in bankruptcy is also analyzed. Ant-Miner algorithm is a application of ant colony optimization and data mining concepts. Qualitative rules generated by ant miner algorithm are validated using measure of agreement. These prediction rules yields better accuracy with lesser number of terms than previously applied qualitative bankruptcy prediction methodologies.

Decision Tree is the most widely applied supervised classification technique. The learning and classification steps of decision tree induction are simple and fast and it can be applied to any domain. In this research student qualitative data has been taken from educational data mining and the performance analysis of the decision tree algorithm ID3, C4.5 and CART are compared. The comparison result shows that the Gini Index of CART influence information Gain Ratio of ID3 and C4.5. The classification accuracy of CART is higher when compared to ID3 and C4.5. However the difference in classification accuracy between the decision tree algorithms is not considerably higher. The experimental results of decision tree indicate that student’s performance also influenced by qualitative factors.