CG-E2S2: Consistency-guaranteed and energy-efficient sleep scheduling algorithm with data aggregation for IoT

Ko, Haneul,Lee, Jaewook,Pack, Sangheon Elsevier 2019 Future generation computer systems Vol.92 No.-

<P><B>Abstract</B></P> <P>In data acquisition (DAQ)-based services of Internet of things (IoT), IoT devices sense and transmit data to the application server through IoT gateway (GW). Due to the energy limitation of IoT devices, it is important to increase their energy efficiency. Further, when data from a very large number of IoT devices is individually transmitted, the data traffic volume can be significant. To resolve these issues, IoT devices and IoT GW can use sleep mode and data aggregation, respectively. However, when the IoT devices are in sleep mode for a long time and/or data are aggregated in IoT GW for a long time without any transmissions, data can become inconsistent. In this paper, we propose a consistency-guaranteed and energy efficient sleep scheduling algorithm (CG-E2S2) with data aggregation. In CG-E2S2, the optimal sleep duration of IoT devices and aggregation duration in IoT GW are jointly determined by means of a Markov decision process (MDP) with the consideration of energy efficiency of IoT devices, data traffic in networks, and data consistency. The evaluation results demonstrate that CG-E2S2 with the optimal policy outperforms the comparison schemes in terms of energy efficiency, data traffic volume, and data consistency.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Sleep and aggregation durations are jointly optimized and determined by Markov decision process. </LI> <LI> Tradeoff between energy efficiency, traffic volume, and data consistency is investigated and optimized. </LI> <LI> Valuable guidelines for designing energy efficient IoT environments are provided. </LI> </UL> </P>

Performance Optimization of Delayed WiFi Offloading in Heterogeneous Networks

Ko, Haneul,Lee, Jaewook,Pack, Sangheon IEEE 2017 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY Vol.66 No.10

<P>In the delayed WiFi offloading, since data are downloaded only through WiFi networks before a predefined delay timer expires, the performance of the delayed WiFi offloading is affected by the delay timer value. To assess the performance of the delayed WiFi offloading, we develop analytical models for the expected saving monetary cost and download completion time. Based on these analytical models, the optimal delay timer is derived to maximally save the monetary cost while maintaining the outage probability on the download time at low level. Evaluation results demonstrate the effects of the average cellular-only residence time and WiFi data rate, and show that better performance can be achieved when the delay timer is set to the optimal value.</P>

Timer-Based Bloom Filter Aggregation for Reducing Signaling Overhead in Distributed Mobility Management

Haneul Ko,Giwon Lee,Sangheon Pack,Kisuk Kweon IEEE 2016 IEEE transactions on mobile computing Vol.15 No.2

<P>Distributed mobility management (DMM) is a promising technology to address the mobile data traffic explosion problem. Since the location information of mobile nodes (MNs) are distributed in several mobility agents (MAs), DMM requires an additional mechanism to share the location information of MNs between MAs. In the literature, multicast or distributed hash table (DHT)-based sharing methods have been suggested; however they incur significant signaling overhead owing to unnecessary location information updates under frequent handovers. To reduce the signaling overhead, we propose a timer-based Bloom filter aggregation (TBFA) scheme for distributing the location information. In the TBFA scheme, the location information of MNs is maintained by Bloom filters at each MA. Also, since the propagation of the whole Bloom filter for every MN movement leads to high signaling overhead, each MA only propagates changed indexes in the Bloom filter when a pre-defined timer expires. To verify the performance of the TBFA scheme, we develop analytical models on the signaling overhead and the latency and devise an algorithm to select an appropriate timer value. Extensive simulation results are given to show the accuracy of analytical models and effectiveness of the TBFA scheme over the existing DMM scheme.</P>

Neighbor-Aware Energy-Efficient Monitoring System for Energy Harvesting Internet of Things

Ko, Haneul,Pack, Sangheon IEEE 2019 IEEE Internet of things journal Vol.6 No.3

<P>In environmental monitoring systems, unnecessary transmissions can occur when an Internet of Things (IoT) device transmits its data without any consideration on neighbors’ transmissions. In this paper, we propose a neighbor-aware energy-efficient monitoring system (NA-EEMS) for energy harvesting IoT devices. In NA-EEMS, to exploit spatial correlation among IoT devices, geographically proximate IoT devices transmit their sensed data in a distributed manner by means of a constraint stochastic game. We devise a best response dynamics-based algorithm to obtain a multipolicy constrained Nash equilibrium. Evaluation results demonstrate that NA-EEMS can improve the network lifetime while preserving the monitoring probability above a desired level.</P>

Coverage-Guaranteed and Energy-Efficient Participant Selection Strategy in Mobile Crowdsensing

Ko, Haneul,Pack, Sangheon,Leung, Victor C. M. IEEE 2019 IEEE Internet of things journal Vol.6 No.2

<P>In mobile crowdsensing (MCS), a participant selection strategy should be carefully designed to guarantee sufficient coverage and avoid unnecessary energy consumption. In this paper, we propose a coverage-guaranteed and energy-efficient participant selection (CG-EEPS) strategy, in which the MCS server determines participants based on the data usage profile and mobility level of mobile devices. In addition, CG-EEPS adopts a piggyback approach of sensory data for energy-efficient transmissions. To attain the optimal performance in CG-EEPS, a constraint Markov decision process (CMDP) problem is formulated and its optimal policy is obtained by a linear programming. To address the curse of dimensionality in CMDP, a greedy heuristic is proposed and evaluated. Trace-driven evaluation results demonstrate that CG-EEPS can achieve sufficient coverage rate only with 20% of participants compared to random selection schemes.</P>

Timer-Based Push Scheme for Online Social Networking Services in Wireless Networks

Haneul Ko,Sangheon Pack,Wonjun Lee IEEE 2012 IEEE communications letters Vol.16 No.12

<P>Nowadays, online social networking services in wireless networks are very popular. In this paper, we propose a timer-based push scheme (TPS) where a number of articles posted during a pre-defined time interval are pushed to users and thus the number of push operations and articles to be pulled can be reduced. We develop an analytical model for TPS and derive the optimal timer minimizing the total cost. Simulation results are given to show the effectiveness of TPS over the existing push N scheme and to validate the analytical results.</P>

A Fair Listen-Before-Talk Algorithm for Coexistence of LTE-U and WLAN

Ko, Haneul,Lee, Jaewook,Pack, Sangheon IEEE 2016 IEEE Transactions on Vehicular Technology VT Vol.65 No.12

<P>Recently, there has been an increasing interest in operating long-term evolution (LTE) in unlicensed bands (i.e., LTE-U). However, since LTE and wireless local area networks (WLANs) are designed to operate in different bands, they have no coexistence mechanism, which leads to significant performance degradation. In particular, since LTE does not sense channel vacancy prior to transmissions, the LTE interference severely affects the WLAN operation. To address this problem, we propose a fair listen-before-talk (F-LBT) algorithm for coexistence of LTE-U and WLAN in unlicensed bands. F-LBT jointly considers the total system throughput and the fairness between LTE-U and WLAN and then allocates an appropriate idle period for WLAN. Evaluation results demonstrate that F-LBT can improve the total system throughput while providing the fairness between LTE-U and WLAN.</P>

Mobility-Aware Vehicle-to-Grid Control Algorithm in Microgrids

Ko, Haneul,Pack, Sangheon,Leung, Victor C. M. IEEE 2018 IEEE transactions on intelligent transportation sy Vol.19 No.7

<P>In a vehicle-to-grid (V2G) system, electric vehicles (EVs) can be efficiently used as power consumers and suppliers to achieve microgrid (MG) autonomy. Since EVs can act as energy transporters among different regions (i.e., MGs), it is an important issue to decide where and when EVs are charged or discharged to achieve the optimal performance in a V2G system. In this paper, we propose a mobility-aware V2G control algorithm (MACA) that considers the mobility of EVs, states of charge of EVs, and the estimated/actual demands of MGs and then determines charging and discharging schedules for EVs. To optimize the performance of MACA, the Markov decision process problem is formulated and the optimal policy on charging and discharging is obtained by a value iteration algorithm. Since the mobility of EVs and the estimated/actual demand profiles of MGs may not be easily obtained, a reinforcement learning approach is also introduced. Evaluation results demonstrate that MACA with the optimal and learning-based policies can effectively achieve MG autonomy and provide higher satisfaction on the charging.</P>

A Software-Defined Surveillance System With Energy Harvesting: Design and Performance Optimization

Ko, Haneul,Pack, Sangheon IEEE 2018 IEEE Internet of things journal Vol.5 No.3

<P>Even though energy harvesting is a promising technology for energy-efficient surveillance systems, energy harvesting levels are highly dynamic depending on the time and location. Thus, the deployment of nonenergy-harvesting sensor nodes (NHSs) and sophisticated sleep scheduling of sensor nodes are necessary for performance guaranteed surveillance systems. In this paper, we present a software-defined surveillance system (SDSS) in which a centralized controller determines the sleep schedules of energy harvesting and NHSs on the basis of the collected information such as the spatial distribution of targets and the energy levels of sensor nodes. To derive the optimal sleep schedules minimizing the number of active sensor nodes while providing sufficient surveillance performance, a constraint Markov decision process problem is formulated and the optimal policy on sleep scheduling is obtained by linear programming. The evaluation results demonstrate that the SDSS with the optimal policy can reduce energy consumption by employing fewer active sensor nodes while providing the required level of target monitoring probability.</P>

Hierarchical Identifier (HID)-based 5G Architecture with Backup Slice

Haneul Ko,Jaewook Lee,Hongrok Choi,Sangheon Pack 한국통신학회 2020 한국통신학회 APNOMS Vol.2020 No.09