TY - GEN
T1 - A Monte Carlo based computation offloading algorithm for feeding robot IoT system
AU - Zhang, Cheng
AU - Ohashi, Takumi
AU - Saijo, Miki
AU - Solis, Jorge
AU - Takeda, Yukio
AU - Lindborg, Ann Louise
AU - Takeda, Ryuta
AU - Tanaka, Yoshiaki
N1 - Funding Information:
This work was carried out as a part of the SICORP under the responsibility of the Japan Science and Technology Agency (JST) and was supported in part by JSPS KAKENHI JP17H03162.
Funding Information:
Acknowledgements. This work was carried out as a part of the SICORP under the responsibility of the Japan Science and Technology Agency (JST) and was supported in part by JSPS KAKENHI JP17H03162.
Publisher Copyright:
© 2018, Springer Nature Switzerland AG.
PY - 2018
Y1 - 2018
N2 - Ageing is becoming an increasingly major problem in European and Japanese societies. We have so far mainly focused on how to improve the eating experience for both frail elderly and caregivers by introducing and developing the eating aid robot, Bestic, made to get the food from plate to the mouth for frail elderly or person with disabilities. We expand the functionalities of Bestic to create food intake reports automatically so as to decrease the undernutrition among frail elderly and workload of caregivers through collecting data via a vision system connected to the Internet of Things (IoT) system. Since the computation capability of Bestic is very limited, computation offloading, in which resource intensive computational tasks are transferred from Bestic to an external cloud server, is proposed to solve Bestic’s resource limitation. In this paper, we proposed a Monte Carlo algorithm based heuristic computation offloading algorithm, to minimize the total overhead of all the Bestic users after we show that the target optimization problem is NP-hard in a theorem. Numeric results showed that the proposed algorithm is effective in terms of system-wide overhead.
AB - Ageing is becoming an increasingly major problem in European and Japanese societies. We have so far mainly focused on how to improve the eating experience for both frail elderly and caregivers by introducing and developing the eating aid robot, Bestic, made to get the food from plate to the mouth for frail elderly or person with disabilities. We expand the functionalities of Bestic to create food intake reports automatically so as to decrease the undernutrition among frail elderly and workload of caregivers through collecting data via a vision system connected to the Internet of Things (IoT) system. Since the computation capability of Bestic is very limited, computation offloading, in which resource intensive computational tasks are transferred from Bestic to an external cloud server, is proposed to solve Bestic’s resource limitation. In this paper, we proposed a Monte Carlo algorithm based heuristic computation offloading algorithm, to minimize the total overhead of all the Bestic users after we show that the target optimization problem is NP-hard in a theorem. Numeric results showed that the proposed algorithm is effective in terms of system-wide overhead.
KW - Computation offloading
KW - Eating robot
KW - IoT
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U2 - 10.1007/978-3-030-05755-8_17
DO - 10.1007/978-3-030-05755-8_17
M3 - Conference contribution
AN - SCOPUS:85058561419
SN - 9783030057541
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 163
EP - 171
BT - Smart Computing and Communication - 3rd International Conference, SmartCom 2018, Proceedings
A2 - Qiu, Meikang
PB - Springer Verlag
T2 - 3rd International Conference on Smart Computing and Communications, SmartCom 2018
Y2 - 10 December 2018 through 12 December 2018
ER -
