中国科学院自动化研究所机构知识库

The Internet of Things (IoT) paradigm has established an efficient platform to enable the collaboration and cooperation of self-configurable and energy-aware IoT nodes for supporting complex applications. Heterogeneous IoT nodes provide various kinds of functionalities, which can be encapsulated and represented as IoT services. These services can be composed to provide value-added services, while spatial-temporal constraints of IoT services should be satisfied, and energy consumption of IoT nodes should be balanced to prolong the network lifetime. Given a set of concurrent service requests, a challenge is to recommend efficient service compositions. To address this challenge, this paper proposes to identify and share common functional components, and thus, to integrate and optimize concurrent requests, where a component corresponds to a snippet of IoT service compositions. Shared components in different requests should not violate their temporal dependencies and thus improving resource utilization. Consequently, composing IoT services with respect to concurrent requests can be reduced to a constrained multi-objective optimization problem, which can be solved by heuristic algorithms. Experimental evaluation has been performed with respect to the state-of-art's algorithms, and the results demonstrate the efficiency and performance of this technique, especially when IoT nodes are relatively large in number and their functionalities are highly overlapped with each other. (C) 2019 Elsevier B.V. All rights reserved.

The Internet of Things (IoT) paradigm has established an efficient platform to enable the collaboration and cooperation of self-configurable and energy-aware IoT nodes for supporting complex applications. Heterogeneous IoT nodes provide various kinds of functionalities, which can be encapsulated and represented as IoT services. These services can be composed to provide value-added services, while spatial-temporal constraints of IoT services should be satisfied, and energy consumption of IoT nodes should be balanced to prolong the network lifetime. Given a set of concurrent service requests, a challenge is to recommend efficient service compositions. To address this challenge, this paper proposes to identify and share common functional components, and thus, to integrate and optimize concurrent requests, where a component corresponds to a snippet of IoT service compositions. Shared components in different requests should not violate their temporal dependencies and thus improving resource utilization. Consequently, composing IoT services with respect to concurrent requests can be reduced to a constrained multi-objective optimization problem, which can be solved by heuristic algorithms. Experimental evaluation has been performed with respect to the state-of-art's algorithms, and the results demonstrate the efficiency and performance of this technique, especially when IoT nodes are relatively large in number and their functionalities are highly overlapped with each other. (C) 2019 Elsevier B.V. All rights reserved.

The Internet of Things (IoT) paradigm has established an efficient platform to enable the collaboration and cooperation of self-configurable and energy-aware IoT nodes for supporting complex applications. Heterogeneous IoT nodes provide various kinds of functionalities, which can be encapsulated and represented as IoT services. These services can be composed to provide value-added services, while spatial-temporal constraints of IoT services should be satisfied, and energy consumption of IoT nodes should be balanced to prolong the network lifetime. Given a set of concurrent service requests, a challenge is to recommend efficient service compositions. To address this challenge, this paper proposes to identify and share common functional components, and thus, to integrate and optimize concurrent requests, where a component corresponds to a snippet of IoT service compositions. Shared components in different requests should not violate their temporal dependencies and thus improving resource utilization. Consequently, composing IoT services with respect to concurrent requests can be reduced to a constrained multi-objective optimization problem, which can be solved by heuristic algorithms. Experimental evaluation has been performed with respect to the state-of-art's algorithms, and the results demonstrate the efficiency and performance of this technique, especially when IoT nodes are relatively large in number and their functionalities are highly overlapped with each other. (C) 2019 Elsevier B.V. All rights reserved.

The Internet of Things (IoT) paradigm has established an efficient platform to enable the collaboration and cooperation of self-configurable and energy-aware IoT nodes for supporting complex applications. Heterogeneous IoT nodes provide various kinds of functionalities, which can be encapsulated and represented as IoT services. These services can be composed to provide value-added services, while spatial-temporal constraints of IoT services should be satisfied, and energy consumption of IoT nodes should be balanced to prolong the network lifetime. Given a set of concurrent service requests, a challenge is to recommend efficient service compositions. To address this challenge, this paper proposes to identify and share common functional components, and thus, to integrate and optimize concurrent requests, where a component corresponds to a snippet of IoT service compositions. Shared components in different requests should not violate their temporal dependencies and thus improving resource utilization. Consequently, composing IoT services with respect to concurrent requests can be reduced to a constrained multi-objective optimization problem, which can be solved by heuristic algorithms. Experimental evaluation has been performed with respect to the state-of-art's algorithms, and the results demonstrate the efficiency and performance of this technique, especially when IoT nodes are relatively large in number and their functionalities are highly overlapped with each other. (C) 2019 Elsevier B.V. All rights reserved.

The Internet of Things (IoT) paradigm has established an efficient platform to enable the collaboration and cooperation of self-configurable and energy-aware IoT nodes for supporting complex applications. Heterogeneous IoT nodes provide various kinds of functionalities, which can be encapsulated and represented as IoT services. These services can be composed to provide value-added services, while spatial-temporal constraints of IoT services should be satisfied, and energy consumption of IoT nodes should be balanced to prolong the network lifetime. Given a set of concurrent service requests, a challenge is to recommend efficient service compositions. To address this challenge, this paper proposes to identify and share common functional components, and thus, to integrate and optimize concurrent requests, where a component corresponds to a snippet of IoT service compositions. Shared components in different requests should not violate their temporal dependencies and thus improving resource utilization. Consequently, composing IoT services with respect to concurrent requests can be reduced to a constrained multi-objective optimization problem, which can be solved by heuristic algorithms. Experimental evaluation has been performed with respect to the state-of-art's algorithms, and the results demonstrate the efficiency and performance of this technique, especially when IoT nodes are relatively large in number and their functionalities are highly overlapped with each other. (C) 2019 Elsevier B.V. All rights reserved.