The Experts below are selected from a list of 3703398 Experts worldwide ranked by ideXlab platform
Ronald Y Chang - One of the best experts on this subject based on the ideXlab platform.
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Design and analysis of multichannel slotted ALOHA for Machine-to-Machine Communication
2015 IEEE Global Communications Conference GLOBECOM 2015, 2015Co-Authors: Chih Hua Chang, Ronald Y ChangAbstract:In Machine-to-Machine (M2M) Communication, a massive number of machine devices may transmit simultaneously in response to an event occurring in the system. Supporting massive device transmission while maintaining low congestion and low access delay is a challenging problem. This paper proposes a new transmission control scheme based on slotted ALOHA, with a practical consideration of partial information available at the data aggregator about the system. The proposed approximate maximum likelihood estimation ALOHA (AMLE-ALOHA) scheme incorporates an approximate ML estimation of the (unknown) number of active machines in the system. We apply the drift analysis to show the stability of the proposed control scheme. Simulation results demonstrate that the proposed AMLE- ALOHA outperforms an existing scheme in terms of the access delay and reaction time under bursty traffic with the same partial information, and compares favorably to the optimal control scheme with oracle knowledge of the number of active machines in the system.
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GLOBECOM - Design and Analysis of Multichannel Slotted ALOHA for Machine-to-Machine Communication
2015 IEEE Global Communications Conference (GLOBECOM), 2015Co-Authors: Chih Hua Chang, Ronald Y ChangAbstract:In Machine-to-Machine (M2M) Communication, a massive number of machine devices may transmit simultaneously in response to an event occurring in the system. Supporting massive device transmission while maintaining low congestion and low access delay is a challenging problem. This paper proposes a new transmission control scheme based on slotted ALOHA, with a practical consideration of partial information available at the data aggregator about the system. The proposed approximate maximum likelihood estimation ALOHA (AMLE-ALOHA) scheme incorporates an approximate ML estimation of the (unknown) number of active machines in the system. We apply the drift analysis to show the stability of the proposed control scheme. Simulation results demonstrate that the proposed AMLE- ALOHA outperforms an existing scheme in terms of the access delay and reaction time under bursty traffic with the same partial information, and compares favorably to the optimal control scheme with oracle knowledge of the number of active machines in the system.
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PIMRC - High-fidelity energy-efficient Machine-to-Machine Communication
2014 IEEE 25th Annual International Symposium on Personal Indoor and Mobile Radio Communication (PIMRC), 2014Co-Authors: Chih Hua Chang, Ronald Y Chang, Hung-yun HsiehAbstract:We consider the correlated data gathering problem in Machine-to-Machine Communications. The machines implement distributed source coding and transmit their gathered data to the data aggregator. The data aggregator has limited radio resources and thus only a subset of machines are selected for transmission. Missing data from nonselected machines are reconstructed at the aggregator by exploiting data correlation. We first propose a data distortion measure based on information loss to characterize the reconstruction, and derive its relationship with the traditional mean squared error distortion analytically. Then, we formulate the machine selection problem with the objective of minimizing the overall data distortion given some resource constraints. We decouple the problem into subproblems and solve them by the proposed algorithm based on the cross entropy method. Numerical results demonstrate improved data fidelity by implementing distributed source coding, and better network coverage and energy efficiency for the proposed machine selection scheme.
Chih Hua Chang - One of the best experts on this subject based on the ideXlab platform.
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Design and analysis of multichannel slotted ALOHA for Machine-to-Machine Communication
2015 IEEE Global Communications Conference GLOBECOM 2015, 2015Co-Authors: Chih Hua Chang, Ronald Y ChangAbstract:In Machine-to-Machine (M2M) Communication, a massive number of machine devices may transmit simultaneously in response to an event occurring in the system. Supporting massive device transmission while maintaining low congestion and low access delay is a challenging problem. This paper proposes a new transmission control scheme based on slotted ALOHA, with a practical consideration of partial information available at the data aggregator about the system. The proposed approximate maximum likelihood estimation ALOHA (AMLE-ALOHA) scheme incorporates an approximate ML estimation of the (unknown) number of active machines in the system. We apply the drift analysis to show the stability of the proposed control scheme. Simulation results demonstrate that the proposed AMLE- ALOHA outperforms an existing scheme in terms of the access delay and reaction time under bursty traffic with the same partial information, and compares favorably to the optimal control scheme with oracle knowledge of the number of active machines in the system.
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GLOBECOM - Design and Analysis of Multichannel Slotted ALOHA for Machine-to-Machine Communication
2015 IEEE Global Communications Conference (GLOBECOM), 2015Co-Authors: Chih Hua Chang, Ronald Y ChangAbstract:In Machine-to-Machine (M2M) Communication, a massive number of machine devices may transmit simultaneously in response to an event occurring in the system. Supporting massive device transmission while maintaining low congestion and low access delay is a challenging problem. This paper proposes a new transmission control scheme based on slotted ALOHA, with a practical consideration of partial information available at the data aggregator about the system. The proposed approximate maximum likelihood estimation ALOHA (AMLE-ALOHA) scheme incorporates an approximate ML estimation of the (unknown) number of active machines in the system. We apply the drift analysis to show the stability of the proposed control scheme. Simulation results demonstrate that the proposed AMLE- ALOHA outperforms an existing scheme in terms of the access delay and reaction time under bursty traffic with the same partial information, and compares favorably to the optimal control scheme with oracle knowledge of the number of active machines in the system.
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PIMRC - High-fidelity energy-efficient Machine-to-Machine Communication
2014 IEEE 25th Annual International Symposium on Personal Indoor and Mobile Radio Communication (PIMRC), 2014Co-Authors: Chih Hua Chang, Ronald Y Chang, Hung-yun HsiehAbstract:We consider the correlated data gathering problem in Machine-to-Machine Communications. The machines implement distributed source coding and transmit their gathered data to the data aggregator. The data aggregator has limited radio resources and thus only a subset of machines are selected for transmission. Missing data from nonselected machines are reconstructed at the aggregator by exploiting data correlation. We first propose a data distortion measure based on information loss to characterize the reconstruction, and derive its relationship with the traditional mean squared error distortion analytically. Then, we formulate the machine selection problem with the objective of minimizing the overall data distortion given some resource constraints. We decouple the problem into subproblems and solve them by the proposed algorithm based on the cross entropy method. Numerical results demonstrate improved data fidelity by implementing distributed source coding, and better network coverage and energy efficiency for the proposed machine selection scheme.
Mario Kusek - One of the best experts on this subject based on the ideXlab platform.
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Agent-Based System for Reliable Machine-to-Machine Communication
Agent and Multi-Agent Systems: Technology and Applications, 2016Co-Authors: Pavle Skocir, Mario Kusek, Gordan JezicAbstract:Reliability is, along with energy efficiency and security, commonly referred to as one of the most important requirements which have to be met to successfully deploy Machine-to-Machine (M2M) Communication systems. We propose an enhancement of agent-based system for M2M Communication which ensures two reliability levels according to the intervals in which data obtained from sensors is sent to back-end system. Our assumption is that Communication reliability is less important for reporting measurements sent with higher frequency than for reporting measurements sent with lower frequency. A mechanism is proposed which determines the appropriate reliability level. Introduced mechanism is implemented on two Libelium Waspmote devices which collect meteorological data in different intervals. Suitability for using one of the two proposed reliability levels is determined according to measured Communication reliability within 24 h and energy consumption data for one operating cycle.
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KES - Context-aware Multi-agent System in Machine-to-Machine Communication☆
Procedia Computer Science, 2014Co-Authors: Hrvoje Maracic, Mario Kusek, Tihana Miskovic, Ignac LovrekAbstract:Abstract Machine-to-Machine (M2 M) Communication refers to Communication among machines without or with only limited human inter- vention. The paper deals with context-awareness in M2 M Communication and proposes rich presence information as a concept to address context information in a multi-agent system supporting networking of machines. Rich Presence Information Data (RPID) extensions suitable for M2 M are introduced into Context-aware Mobile Agent Network model. Case study describing context information related to energy consumption and energy saving is presented. Results based on simulations and measurements in a laboratory test-bed are discussed.
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17 th International Conference in Knowledge Based and Intelligent Information and Engineering Systems - KES2013 Rich Presence Information in Agent Based Machine-to-Machine Communication
2013Co-Authors: Mario Kusek, Ignac Lovrek, Hrvoje MaracicAbstract:Abstract Machine-to-Machine (M2M) Communication is characterized by Communication between two or more entities that do notneed human intervention in a heterogeneous environment. M2M entities in some cases need to turn off Communication inorder to preserve energy in which cases other entities can not communicate with them. The M2M entities can be aware ofsuch context information and utilize it to perform optimisation in Communication. Such information is defined as rich presenceinformation and is used in this paper. The paper extends the mobile agent network with presence context information andapplies it in experiments.c 2013 The Authors. Published by Elsevier B.V.Selection and peer-review under responsibility of KES International.Keywords: Machine-to-Machine Communication; presence; agent; multi-agent system 1. IntroductionMachine-to-Machine (M2M) Communication is Communication between machines that do not necessarilyneed any direct human intervention. Machines can be devices such as: computers, mobile phones, tablets, sensors,smart grid network elements, embedded processors, cars, industrial and medical equipment, and countless othereveryday devices. In such an environment, some devices are powered by batteries and need to run for a longperiod of time without charging or battery change. Consequently, machines must efficiently use energy by turningoff Communication when it is not necessary. To address this power efficiency challenge and enable machinesto regulate their power consumption, it is necessary to have available the information about a machine’s stateand context information from environment. By introducing intelligence into a decision making process machinewill further improve energy efficiency. We evaluate rich presence as a tool to address the availability of contextinformation, and program agents as a way to enable intelligent decision making.This paper is organized as follows. In Section 2, rich presence information is introduced as a type of contextinformation that will be used in the M2M system (Section 3). Section 4 reports on related work, while the formalMobile Agent Network Model is explained in Section 5 and extended with presence information as context.Section 6 presents a case study based on the Mobile Agent Network Model extension and conducted experiments.Section 7 concludes the paper.
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KES - Rich Presence Information in Agent based Machine-to-Machine Communication
Procedia Computer Science, 2013Co-Authors: Mario Kusek, Ignac Lovrek, Hrvoje MaracicAbstract:Abstract Machine-to-Machine (M2 M) Communication is characterized by Communication between two or more entities that do not need human intervention in a heterogeneous environment. M2 M entities in some cases need to turn off Communication in order to preserve energy in which cases other entities can not communicate with them. The M2 M entities can be aware of such context information and utilize it to perform optimisation in Communication. Such information is defined as rich presence information and is used in this paper. The paper extends the mobile agent network with presence context information and applies it in experiments.
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basic principles of machine to machine Communication and its impact on teleCommunications industry
International Convention on Information and Communication Technology Electronics and Microelectronics, 2011Co-Authors: Vedran Galetic, Iva Bojic, Mario Kusek, Gordan Jezic, Sasa Desic, Darko HuljenicAbstract:It has been estimated that by the end of 2020 there will be 50 billion connected devices world-wide. Such projections entice the industry to explore and tap a wide range of opportunities that the M2M (Machine-to-Machine) Communication concept offers, enabling novel business cases, enhanced workflow efficiency and improved quality of life. It is therefore no surprise that prominent teleCommunication association and standardisation bodies such as 3GPP and ETSI are largely involved in providing standards and recommendations in the context of M2M Communication. In order to engage in the prospective area of M2M and fully exploit its potential, a thorough understanding of M2M basic architecture and principles is essential. A systematic approach is also necessary in continuously keeping track of current M2M related activities and achievements by industrial parties of various verticals such as automotive, healthcare, transport etc. This paper brings forward an overview of M2M basic architecture and principles, development of standards and proposed requirements, as well as an insight into its current industry adoption accompanied by a selection of specific examples.
Hrvoje Maracic - One of the best experts on this subject based on the ideXlab platform.
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KES - Context-aware Multi-agent System in Machine-to-Machine Communication☆
Procedia Computer Science, 2014Co-Authors: Hrvoje Maracic, Mario Kusek, Tihana Miskovic, Ignac LovrekAbstract:Abstract Machine-to-Machine (M2 M) Communication refers to Communication among machines without or with only limited human inter- vention. The paper deals with context-awareness in M2 M Communication and proposes rich presence information as a concept to address context information in a multi-agent system supporting networking of machines. Rich Presence Information Data (RPID) extensions suitable for M2 M are introduced into Context-aware Mobile Agent Network model. Case study describing context information related to energy consumption and energy saving is presented. Results based on simulations and measurements in a laboratory test-bed are discussed.
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17 th International Conference in Knowledge Based and Intelligent Information and Engineering Systems - KES2013 Rich Presence Information in Agent Based Machine-to-Machine Communication
2013Co-Authors: Mario Kusek, Ignac Lovrek, Hrvoje MaracicAbstract:Abstract Machine-to-Machine (M2M) Communication is characterized by Communication between two or more entities that do notneed human intervention in a heterogeneous environment. M2M entities in some cases need to turn off Communication inorder to preserve energy in which cases other entities can not communicate with them. The M2M entities can be aware ofsuch context information and utilize it to perform optimisation in Communication. Such information is defined as rich presenceinformation and is used in this paper. The paper extends the mobile agent network with presence context information andapplies it in experiments.c 2013 The Authors. Published by Elsevier B.V.Selection and peer-review under responsibility of KES International.Keywords: Machine-to-Machine Communication; presence; agent; multi-agent system 1. IntroductionMachine-to-Machine (M2M) Communication is Communication between machines that do not necessarilyneed any direct human intervention. Machines can be devices such as: computers, mobile phones, tablets, sensors,smart grid network elements, embedded processors, cars, industrial and medical equipment, and countless othereveryday devices. In such an environment, some devices are powered by batteries and need to run for a longperiod of time without charging or battery change. Consequently, machines must efficiently use energy by turningoff Communication when it is not necessary. To address this power efficiency challenge and enable machinesto regulate their power consumption, it is necessary to have available the information about a machine’s stateand context information from environment. By introducing intelligence into a decision making process machinewill further improve energy efficiency. We evaluate rich presence as a tool to address the availability of contextinformation, and program agents as a way to enable intelligent decision making.This paper is organized as follows. In Section 2, rich presence information is introduced as a type of contextinformation that will be used in the M2M system (Section 3). Section 4 reports on related work, while the formalMobile Agent Network Model is explained in Section 5 and extended with presence information as context.Section 6 presents a case study based on the Mobile Agent Network Model extension and conducted experiments.Section 7 concludes the paper.
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KES - Rich Presence Information in Agent based Machine-to-Machine Communication
Procedia Computer Science, 2013Co-Authors: Mario Kusek, Ignac Lovrek, Hrvoje MaracicAbstract:Abstract Machine-to-Machine (M2 M) Communication is characterized by Communication between two or more entities that do not need human intervention in a heterogeneous environment. M2 M entities in some cases need to turn off Communication in order to preserve energy in which cases other entities can not communicate with them. The M2 M entities can be aware of such context information and utilize it to perform optimisation in Communication. Such information is defined as rich presence information and is used in this paper. The paper extends the mobile agent network with presence context information and applies it in experiments.
Miguel Franklin De Castro - One of the best experts on this subject based on the ideXlab platform.
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ISCC - A mechanism to control the congestion in Machine-to-Machine Communication in LTE-A networks
2017 IEEE Symposium on Computers and Communications (ISCC), 2017Co-Authors: David Aragao, Dario Vieira, Miguel Franklin De CastroAbstract:Machine-to-Machine Communication (M2M) is a core elements in the Internet of Things (IoT) vision. Due to the large number of devices expected, the Long-term Evolution-Advanced (LTA-A) networks may present congestion and overload problems. In this paper, we present two approaches to mitigate the impact of M2M Communication in LTE-A. We model such overloaded scenario as a bankruptcy problem and apply two strategies to define how resources should be allocated. The simulation results show that our approaches present improvements in terms of energy efficiency, impact control of M2M over Human-to-human (H2H) and define priority among different classes of device.
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A fair QoS-aware dynamic LTE scheduler for Machine-to-Machine Communication
Computer Communications, 2016Co-Authors: Adyson M. Maia, Dario Vieira, Miguel Franklin De Castro, Yacine Ghamri-doudaneAbstract:The long term evolution (LTE) standard plays an important role in the development of internet of things (IoT) and Machine-to-Machine (M2M) Communication because of its high data rates, low latency, high flexibility and low cost. However, improvements are needed in the network to support the uplink-heavy traffic generated by M2M Communication and also to ensure the diversity of service requirements of this Communication and to control the performance reduction in the classical mobile services of human-to-human (H2H) Communication. In this paper, we present a new LTE uplink scheduler that dynamically adjusts to the level of congestion of the network based on the current traffic information of each device to support the M2M traffic. Furthermore, the main goals of our approach are (i) satisfy the quality of service (QoS) requirements, (ii) ensure fair allocation of resources and (iii) control the impact of H2H traffic performance. The simulation results demonstrated that the proposed scheduling has good performance according to the three objectives aforementioned.
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PIMRC - A dynamic LTE uplink packet scheduler for Machine-to-Machine Communication
2014 IEEE 25th Annual International Symposium on Personal Indoor and Mobile Radio Communication (PIMRC), 2014Co-Authors: Adyson M. Maia, Miguel Franklin De Castro, Dario VieiraAbstract:The Long Term Evolution (LTE) standard plays an important role in the development of Machine-to-Machine (M2M) Communication. However, the M2M Communication has several different characteristics regarding to Human-to-Human (H2H) Communication. Therefore, the shortage of radio resources, satisfaction of the Quality of Service (QoS) requirements and the reduction of the H2H traffic performance are important issues to be addressed when introducing the M2M Communication in the network. In this article, we present a scheduler that may dynamically adjust to the level of congestion of the network based on the current traffic information of each device. The main goals of our approach are (i) satisfy the QoS requirements (ii) ensure fair allocation of resources and (iii) control the impact of H2H traffic performance. The simulation results demonstrated that the proposed scheduling has good performance according to the three objectives aforementioned.
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SBRC - Toward a New LTE Uplink Packet Scheduler for Machine-to-Machine Communication
2014 Brazilian Symposium on Computer Networks and Distributed Systems, 2014Co-Authors: Adyson M. Maia, Dario Vieira, Miguel Franklin De Castro, Yacine Ghamri-doudaneAbstract:This paper proposes a mechanism for uplink packet scheduler in LTE network in the context of Machine-to-Machine (M2M) Communications that uses the current and past information of the system to satisfy the Quality of Service (QoS) requirements, ensure fairness in the allocation of resources and control the congestion caused by the M2M devices. The results indicate that the proposed approach can reduce the impact of M2M Communication on the Human-to-Human (H2H) Communication and avoid the problem of starvation.
