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The statistics on worldwide IoT-connected devices predicts that the number of IoT devices will rise up to 60 billion by 2025. To meet the advancement which can ensure a competitive global Success and can promote continual improvement, Internet of Things (IoT) devices play an important role. One of the most recent changes in the communication technology is the paradigm shift from traditional systems to software-driven ones. In this context, IoT provides plenty of opportunities to pioneer new products and influence interconnected systems with large scalability. IoT-driven intelligent devices that are capable of performing automatic updates are very much required in the present scenario. Main problems with the companies building these devices are that non-functional aspects of these devices which will lead to device-related security risks were not given much importance. So as a result, device manufacturers have to take into considerations of various non-functional aspects when designing their products such as security, safety, scalability, reliability and performance. This paper proposes a layered IoT framework with a focus on non-functional testing aspects in order to enable the organizations to demonstrate themselves in leveraging the maximum potential in developing smarts products and stability in their business performance.

Risk based thinking is the core aspect to avoid or reduce the undesired effects and promote continual improvement for any organization, especially in the field of higher education. Preventive action becomes an automatic process when a management system is risk-based. The contingency approach to management will make fruitful results once it is considered as more explicit and builds it into strategic plan of the management system with upfront planning with the help of business models. In the strategic plan of any organization, leadership and administration plays an important role. By identifying the context related risks, leaders can analyze the opportunities in terms of impact and feasibility and plan towards prioritizing the risks to act on. In this direction, the need for a business model which focuses on efficient process-based approach towards risk prioritization, thereby prevention and avoidance is proposed, which demonstrates management their leadership, and commitment to the quality management of higher education.

Internet of things (IoT) is a new trending paradigm for advanced technological development which has drawn significant research attention in the recent years. IoT comprises intelligent communicating “things,” putting a big challenge on ensuring security, reliability, efficiency, and safety in their interaction. Staying connected always, constant evolution, and grappling with multiple life cycles are the major factors of concern. In this context, a new process model for IoT-based software development has a greater relevance in order to reduce the associated risk. To exploit the capability of IoT-driven innovations which enable organizations to enhance their revenue streams, reduce time to market while increasing business agility, organizations need to determine how best to employ IoT-enabled business models that promote sustainable competitive advantage.

Mobile cloud computing is a technique or model in which mobile applications are built, powered and hosted using cloud computing technology. In Mobile Cloud computing we can store information regarding sender, data and receiver on cloud through mobile application. As we store more and more information on cloud by client, security issue will arise. This chapter presents a review on the mobile cloud computing concepts as well as security issues and vulnerabilities affecting Cloud Systems and the possible solutions available to such issues within the context of cloud computing. It also describes the pros and cons of the existing security strategy and also introduces the existing issues in cloud computing such as data integrity, data segregation, and security.

The financial services industry is changing rapidly as a result of advances in information technology, telecommunications and the Internet. Technological innovations and increasing customer demand have led to the emergence of new services and new organizational forms for financial services firms. The gait of innovation in the Social media, the payment system is staggering. The biggest social media sites are Facebook, massive and used by almost everyone, Twitter, the micro-blogging, and LinkedIn, the online professional networking site. By using the social media connections as a method to exchange the funds, we can integrate our use of mobile wallets, PayPal, etc. to our social media sites. Believing on daily deal platforms, none of the current daily deal platforms can compete with the granularity and relevance with which banks could target a deal to a specific subscriber, having access to their extensive spending history and preferences. A feedback loop extending from the Bank to the merchants enabling the creation of accurate list of customers who consistently spend in specific retail categories can help merchants in delivering targeted offers to attract new customers.

The changing market trends make it mandatory for businesses to constantly innovate and improve while keeping the expenditures at lowest. For any business, irrespective of size, information technology is playing a major role. Cloud computing is emerging as a driving factor for all types of businesses. Although cloud computing is widely recognized as a technology transformer, its potential for driving business innovation is not exploited to the fullest. Cloud computing promises to decrease capital expenditures and offer higher utilization rates on existing hardware. To exploit the cloud computing capability to enable organizations to enhance their revenue streams and improved customer relationships while increasing business agility, organizations need to determine how best to employ cloud enabled business models that promote sustainable competitive advantage, as this chapter discusses. By completely leveraging cloud computing opportunities, organizations can focus on process improvement by driving inefficiencies out of repeatable processes and providing agility to reuse elements of business logic.

Software development methods are attempting to offer an eager business community lightweight and faster solutions in the latest advancement in the software development world, which includes the practice of Cloud Computing, Service Oriented Engineering (SOE), and Agile and Lean approaches in software development.

The mobile payment is the one of the most promising future applications in the domain of mCommerce. Different approaches come to the market and try to address existing needs, but up to day no global solution exists. The proposed system would enhance the P2P (SMS Based) mobile Payment system, which will try to ease the money transfer between two individual. This solution the key difference is the time needed to inform the beneficiary about the completion of the payment. The advantage of such a system is that only the mobile phone number, not the bank account number or credit card details, are transmitted. Moreover, consumers can even request a proposed system's phone number if they do not feel comfortable giving their mobile phone number to merchants. Therefore, proposed system tries to improve the customer's trust and payment security.

The overriding goal of software engineering is to provide a high quality system, application or a product. To achieve this goal, software engineers must apply effective methods coupled with modern tools within the context of a mature software process [2]. In addition, it is also must to assure that high quality is realized. Although many quality measures can be collected at the project levels, the important measures are errors and defects. Deriving a quality measure for reusable components has proven to be challenging task now a days. The results obtained from the study are based on the empirical evidence of reuse practices, as emerged from the analysis of industrial projects. Both large and small companies, working in a variety of business domains, and using object-oriented and procedural development approaches contributed towards this study. This paper proposes a quality metric that provides benefit at both project and process level, namely defect removal efficiency (DRE)., {"references":["Kimberly Jordan, MJY Team, George Mason University, \"Software\nReuse Term Paper For The MJY Team\", Software Risk Management\nWWW SITE, Apr.1997.","Roger S Pressman, Software Engineering-A practitioner-s\napproach, 5th Edition, McGraw-Hill, 2001.","V. Basili, L. Briand, and W. Melo., \"Measuring the impact of reuse on\nquality and productivity in object-oriented systems.\" Technical Report\nCS- TR-3395, University of Maryland, Computer Science Department,\n1995.","Barnes, B. H., Bollinger, T. B., \"Making Reuse Cost-Effective,\" IEEE\nSoftware, Vol. 8, Number 1, January 1991, pp. 642-652.","J. E. Gaffney, Jr., R. D. Cruickshank, \"A general economics model of\nsoftware reuse\", Proceedings of the 14th international conference on\nSoftware engineering, Melbourne, Australia, May 11-15, 1992, pp.327-\n337.","Fonash P., \" Metrics For Reusable Software Code Components\", PhD\nDissertation, George mason University, Fairfax, Virginia, 1993.","Parastoo Mohagheghi, Reidar Conradi, Ole M. Killi, Henrik Schwarz,\n\"An Empirical Study of Software Reuse vs. Defect- Density and\nStability\", Simula Research Laboratory, P.O.Box 134, NO-1325\nLysaker, Norway.","Lubars MD, Affording Higher Reliability Through Software Reusability,\nSoftware Eng. Notes, Oct. 1986.","Fenton, N.E., Ohlsson, N., \"Quantitative Analysis of Faults and\nFailures in a Complex Software System\", IEEE Trans. Software\nEngineering, 26(8), 2000, pp. 797-814.\n[10] Malaiya, K.Y., Denton, J., \"Module Size Distribution and Defect\nDensity\", Proc. 11th International Symposium on Software Reliability\nEngineering- ISSRE-00, 2000, pp. 62-71.\n[11] Fonash P., \"Metrics For Reusable Software Code Components\", PhD\nDissertation, George mason University, Fairfax, Virginia, 1993.\n[12] Sherriff, M., Nagappan, N., Williams, L., and Vouk, M. A., \"Early\nEstimation of Defect Density Using an In-Process Haskell Metrics\nModel,\" First International Workshop on Advances in Model-Based\nSoftware Testing, St. Louis, MO, May 15-21, 2005."]}

Component-Based software engineering provides an opportunity for better quality and increased productivity in software development by using reusable software components [10]. One of the most critical aspects of the quality of a software system is its performance. The systematic application of software performance engineering techniques throughout the development process can help to identify design alternatives that preserve desirable qualities such as extensibility and reusability while meeting performance objectives [1]. In the present scenario, software engineering methodologies strongly focus on the functionality of the system, while applying a "fix- it-later" approach to software performance aspects [3]. As a result, lengthy fine-tunings, expensive extra hard ware, or even redesigns are necessary for the system to meet the performance requirements. In this paper, we propose design based, implementation independent, performance prediction approach to reduce the overhead associated in the later phases while developing a performance guaranteed software product with the help of Unified Modeling Language (UML)., {"references":["Mangano, \"An Approach to Performance Evaluation of Software\nArchitectures\", Workshop on Software and Performance, Santa Fe, NM,\nACM, 1998, pp. 178-190.","B. W. Boehm, \"Verifying and Validating Software Requirements and\nDesign Specifications,\" IEEE Software, vol. 1, no. 1, pp. 75-88, 1984.","Tom Verdict, Bart Dhoedt, Frank Gielen, and Piet Demeester, Senior\nmember, IEEE, \" automatic Inclusion Of Middleware Performance\nAttributes into Architectural UML Software Models\", IEEE Trans. On\nSoft.Engg. VOL 31,no.8, August 2005.","D.E. Harms and B.W. Weide, \"Copying and Swapping: Influences on\nthe Design of Reusable Software Components\", IEEE Trans. Soft. Eng.\n17, 5 (1991), 424-43s.","Yan liu, Member, IEEE, Alan Fekete, Member IEEE Computer Society,\nand Ian Gorton, Member, IEEE, \"Design-Level Performance prediction\nof Component-Based Applications\", IEEE Trans. On Soft.Engg. VOL\n31,no.11, November 2005.","G. Booch, J. Rumbaugh, and I. Jacobson, The Unified Modeling\nLanguage, User Guide, Reading, MA, Addison Wesley, 1999.","V.Cortelessa, A, D-Ambrogio, and G.Iazolla, \"Automatic Derivation of\nsoftware performance models from case Documents\", performance\nevaluation, vol.45, no.s 2-3,pp.81-105, July 2001.","P.G. Gu and D.C. Petriu, \"XSLT transformation from UML Model to\nLQN performance models\", proc. Third Int-l workshop Software\nperformance (WOSP ÔÇÿ2002), pp.227-234.July 2002.","R. Kazman, et al., \"Scenario-Based Analysis of Software Architecture\",\nIEEE Software, vol. 13, no. 6, 1996, pp.47-55.\n[10] X.Wu and M. Woodside, \"Performance Modeling from Software\ncomponents\", proceedings of the Fourth International Workshop on\nSoftware and Performance, pp.290-301, 2004.\n[11] Balsamo and Mangano 1998] S. Balsamo, P. Inverardi, and C. Mangano,\n\"An Approach to Performance Evaluation of Software Architectures\",\nWorkshop on Software and Performance, Santa Fe, NM, ACM, 1998,\npp. 178-190.\n[12] C. U. Smith, Performance Engineering of Software Systems, Reading,\nMA, Addison-Wesley, 1990.\n[13] Sitaraman M., et al., \"Performance specification of software\ncomponents\", Proc. of SSR '01, p. 310. ACM/SIGSOFT, May 2001.\n[14] Connie U. Smith and Lloyd G. Williams, Responsive, Scalable Systems:\nPractical Performance Engineering for Object-Oriented Software, 2001.\n[15] Cortellessa, V., Mirandola, R. PRIMA-UML: a Performance Validation\nIncremental Methodology on Early UML Diagrams, Science of\nComputer Programming, 44 (2002), 101-129, July 2002, Elsevier\nScience.\n[16] Lavenberg S.S. Computer Performance Modeling Handbook, Academic\nPress, New York, 1983.\n[17] UML Profile for Schedulability, Performance, and Time Specification:\nttp://cgi.omg.org/docs/ptc/02-03-02.pdf.\n[18] UML Documentation version 1.4 Web site. Online\nhttp://www.rational.com/uml/resources/documentation/.\n[19] Crnkovic, I. and Larsson, M. \"A Case Study: Demands on Componentbased\nDevelopment\", Proceedings 22nd International Conference on\nSoftware Engineering, ACM Press, 2000."]}