Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

Mobile Crowd Sensing in Edge Computing Environment

abstract: The mobile crowdsensing (MCS) applications leverage the user data to derive useful information by data-driven evaluation of innovative user contexts and gathering of information at a high data rate. Such access to context-rich data can potentially enable computationally intensive crowd-sourcing applications such as tracking a missing person or capturing a highlight video of an event. Using snippets and pictures captured from multiple mobile phone cameras with specific contexts can improve the data acquired in such applications. These MCS applications require efficient processing and analysis to generate results in real time. A human user, mobile device and their interactions cause a change in context on the mobile device affecting the quality contextual data that is gathered. Usage of MCS data in real-time mobile applications is challenging due to the complex inter-relationship between: a) availability of context, context is available with the mobile phones and not with the cloud, b) cost of data transfer to remote cloud servers, both in terms of communication time and energy, and c) availability of local computational resources on the mobile phone, computation may lead to rapid battery drain or increased response time. The resource-constrained mobile devices need to offload some of their computation. This thesis proposes ContextAiDe an end-end architecture for data-driven distributed applications aware of human mobile interactions using Edge computing. Edge processing supports real-time applications by reducing communication costs. The goal is to optimize the quality and the cost of acquiring the data using a) modeling and prediction of mobile user contexts, b) efficient strategies of scheduling application tasks on heterogeneous devices including multi-core devices such as GPU c) power-aware scheduling of virtual machine (VM) applications in cloud infrastructure e.g. elastic VMs. ContextAiDe middleware is integrated into the mobile application via Android API. The evaluation consists of overheads and costs analysis in the scenario of ``perpetrator tracking" application on the cloud, fog servers, and mobile devices. LifeMap data sets containing actual sensor data traces from mobile devices are used to simulate the application run for large scale evaluation.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

A Self-Reconfigurable Framework for Context Awareness

Urban environments are increasingly pervaded by ICT devices. Soon, citizens and technologies could collaboratively constitute large-scale socio-technical organisms supporting both individual and collective awareness. This paper illustrates a modern awareness framework designed to deal with the complexity of this scenario. The framework is able to collect and classify data streams in a modular way by supporting service oriented, reconfigurable components. Furthermore, we evaluate an innovative meta-classifcation scheme based on state-automata for (i) improving energy efficiency, (ii) improving classification accuracy and (iii) improving software engineering of aware systems, without affecting the overall performance

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Power Consumption Analysis, Measurement, Management, and Issues:A State-of-the-Art Review of Smartphone Battery and Energy Usage

The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone's energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device's energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone's power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones' batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed

Raamistik mobiilsete asjade veebile

Internet on oma arengus läbi aastate jõudnud järgmisse evolutsioonietappi - asjade internetti (ingl Internet of Things, lüh IoT). IoT ei tähista ühtainsat tehnoloogiat, see võimaldab eri seadmeil - arvutid, mobiiltelefonid, autod, kodumasinad, loomad, virtuaalsensorid, jne - omavahel üle Interneti suhelda, vajamata seejuures pidevat inimesepoolset seadistamist ja juhtimist. Mobiilseadmetest nagu näiteks nutitelefon ja tahvelarvuti on saanud meie igapäevased kaaslased ning oma mitmekülgse võimekusega on nad motiveerinud teadustegevust mobiilse IoT vallas. Nutitelefonid kätkevad endas võimekaid protsessoreid ja 3G/4G tehnoloogiatel põhinevaid internetiühendusi. Kuid kui kasutada seadmeid järjepanu täisvõimekusel, tühjeneb mobiili aku kiirelt. Doktoritöö esitleb energiasäästlikku, kergekaalulist mobiilsete veebiteenuste raamistikku anduriandmete kogumiseks, kasutades kergemaid, energiasäästlikumaid suhtlustprotokolle, mis on IoT keskkonnale sobilikumad. Doktoritöö käsitleb põhjalikult energia kokkuhoidu mobiilteenuste majutamisel. Töö käigus loodud raamistikud on kontseptsiooni tõestamiseks katsetatud mitmetes juhtumiuuringutes päris seadmetega.The Internet has evolved, over the years, from just being the Internet to become the Internet of Things (IoT), the next step in its evolution. IoT is not a single technology and it enables about everything from computers, mobile phones, cars, appliances, animals, virtual sensors, etc. that connect and interact with each other over the Internet to function free from human interaction. Mobile devices like the Smartphone and tablet PC have now become essential to everyday life and with extended capabilities have motivated research related to the mobile Internet of Things. Although, the recently developed Smartphones enjoy the high performance and high speed 3G/4G mobile Internet data transmission services, such high speed performances quickly drain the battery power of the mobile device. This thesis presents an energy efficient lightweight mobile Web service provisioning framework for mobile sensing utilizing the protocols that were designed for the constrained IoT environment. Lightweight protocols provide an energy efficient way of communication. Finally, this thesis highlights the energy conservation of the mobile Web service provisioning, the developed framework, extensively. Several case studies with the use of the proposed framework were implemented on real devices and has been thoroughly tested as a proof-of-concept.https://www.ester.ee/record=b522498