The Internet of Things (IoT) is a technological revolution that has changed everything we do and given us a new perspective on our daily lives, but despite the fact that numerous publications have focused on characterizing the many edges and technologies that make up an IoT system, the IoT ecosystem is still seen as too complex to be recognized as a stand-alone environment due to its significant diversity; hence, the objective of this research is to address such a complex environment in a way that highlights its components and distinguishes them both individually and in relation to their broader context. Therefore, the definition of IoT and its emergence were discussed and organized around the timeline of Internet development phases demonstrating that IoT has been a need that has accompanied the presence of the Internet since its early stages, and then its growth and impact were discussed and highlighted with estimates and numbers. On the technical side, each of the following groups, IoT components, protocols, and architectures, was defined, discussed, and grouped in such a way that their intergroup organization, as well as their placement and contribution to the overall ecosystem, was highlighted. This, in addition to the various examples mentioned throughout the discussion, will provide the reader with a better understanding of the Internet of Things and how deeply it has become entwined in our daily lives and routines as a result of its numerous applications.
This paper tackles the concept of key performance indicators (KPI) that is being hosted in almost all software systems, trying to make use computer systems and algorithms to optimize and help concerned parties with more efficient analysis of data being given to them. Since designing these KPI systems follows up to a given extent a common pattern, and even diverge in a certain systematic approach. Based on a practical corporate project, and after having summarized related literature reviews, this paper attempts to suggest an as generic as possible approach that can be used by developers to implement KPI systems using data-warehouses and Business Intelligence (BI) in a most optimal way, to lead the technical focus towards thorough and tricky implementation of business requirements.
One of the many problems that are considered to be NP-Hard is the Multiple Sequence Alignment one that initially requires, as for any other of its siblings, a specific encoding schema and design of the main functionalities of the heuristics algorithm being implemented and executed. This paper intends to discuss our proposed generic implementation of the Simulated Annealing, inspired for the procedure of cooling and shaping methods of metals. In our algorithm, we attempted to add some executions tracing functionalities in order to help later analysis for initial parameters tuning. On another hand, we also tried to get closer in our attempt to mimic the cooling of metals, but giving it an option to run under different cooling schedules. We proposed a few schedules that seemed to be studied and/or used in many algorithm implementations.
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