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Added by
Matthias Brust R.
Publication date
2007
fields
Informatics Engineering
and research's language is
English
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No Arabic abstract
Leveraging the potential power of even small handheld devices able to communicate wirelessly requires dedicated support. In particular, collaborative applications need sophisticated assistance in terms of querying and exchanging different kinds of data. Using a concrete example from the domain of mobile learning, the general need for information dissemination is motivated. Subsequently, and driven by infrastructural conditions, realization strategies of an appropriate middleware service are discussed.
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Internet of Things (IoT) is an Internet-based environment of connected devices and applications. IoT creates an environment where physical devices and sensors are flawlessly combined into information nodes to deliver innovative and smart services for human-being to make their life easier and more efficient. The main objective of the IoT devices-network is to generate data, which are converted into useful information by the data analysis process, it also provides useful resources to the end users. IoT resource management is a key challenge to ensure the quality of end user experience. Many IoT smart devices and technologies like sensors, actuators, RFID, UMTS, 3G, and GSM etc. are used to develop IoT networks. Cloud Computing plays an important role in these networks deployment by providing physical resources as virtualized resources consist of memory, computation power, network bandwidth, virtualized system and device drivers in secure and pay as per use basis. One of the major concerns of Cloud-based IoT environment is resource management, which ensures efficient resource utilization, load balancing, reduce SLA violation, and improve the system performance by reducing operational cost and energy consumption. Many researchers have been proposed IoT based resource management techniques. The focus of this paper is to investigate these proposed resource allocation techniques and finds which parameters must be considered for improvement in resource allocation for IoT networks. Further, this paper also uncovered challenges and issues of Cloud-based resource allocation for IoT environment.
Ubiquitous computing based on small mobile devices using wireless communication links is becoming very attractive. The computational power and storage capacities provided allow the execution of sophisticated applications. Due to the fact that sharing of information is a central problem for distributed applications, the development of self organizing middleware services providing high level interfaces for information managing is essential. ADS is a directory service for mobile ad-hoc networks dealing with local and nearby information as well as providing access to distant information. The approach discussed throughout this paper is based upon the concept of information markets.
Complex Event Processing (CEP) is a powerful paradigm for scalable data management that is employed in many real-world scenarios such as detecting credit card fraud in banks. The so-called complex events are expressed using a specification language that is typically implemented and executed on a specific runtime system. While the tight coupling of these two components has been regarded as the key for supporting CEP at high performance, such dependencies pose several inherent challenges as follows. (1) Application development atop a CEP system requires extensive knowledge of how the runtime system operates, which is typically highly complex in nature. (2) The specification language dependence requires the need of domain experts and further restricts and steepens the learning curve for application developers. In this paper, we propose CEPLESS, a scalable data management system that decouples the specification from the runtime system by building on the principles of serverless computing. CEPLESS provides operator as a service and offers flexibility by enabling the development of CEP application in any specification language while abstracting away the complexity of the CEP runtime system. As part of CEPLESS, we designed and evaluated novel mechanisms for in-memory processing and batching that enables the stateful processing of CEP operators even under high rates of ingested events. Our evaluation demonstrates that CEPLESS can be easily integrated into existing CEP systems like Apache Flink while attaining similar throughput under a high scale of events (up to 100K events per second) and dynamic operator update in up to 238 ms.
Mobile system-on-chips (SoCs) are growing in their complexity and heterogeneity (e.g., Arms Big-Little architecture) to meet the needs of emerging applications, including games and artificial intelligence. This makes it very challenging to optimally manage the resources (e.g., controlling the number and frequency of different types of cores) at runtime to meet the desired trade-offs among multiple objectives such as performance and energy. This paper proposes a novel information-theoretic framework referred to as PaRMIS to create Pareto-optimal resource management policies for given target applications and design objectives. PaRMIS specifies parametric policies to manage resources and learns statistical models from candidate policy evaluation data in the form of target design objective values. The key idea is to select a candidate policy for evaluation in each iteration guided by statistical models that maximize the information gain about the true Pareto front. Experiments on a commercial heterogeneous SoC show that PaRMIS achieves better Pareto fronts and is easily usable to optimize complex objectives (e.g., performance per Watt) when compared to prior methods.
Technical advances in ubiquitous sensing, embedded computing, and wireless communication are leading to a new generation of engineered systems called cyber-physical systems (CPS). CPS promises to transform the way we interact with the physical world just as the Internet transformed how we interact with one another. Before this vision becomes a reality, however, a large number of challenges have to be addressed. Network quality of service (QoS) management in this new realm is among those issues that deserve extensive research efforts. It is envisioned that wireless sensor/actuator networks (WSANs) will play an essential role in CPS. This paper examines the main characteristics of WSANs and the requirements of QoS provisioning in the context of cyber-physical computing. Several research topics and challenges are identified. As a sample solution, a feedback scheduling framework is proposed to tackle some of the identified challenges. A simple example is also presented that illustrates the effectiveness of the proposed solution.
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