TY - CHAP
T1 - Energy management for CPS
AU - Liu, Chi Harold
N1 - Publisher Copyright:
© 2016 by Taylor and Francis Group, LLC.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - The previous three chapters address different aspects of the architectures of CPS. However, there are various technical challenges in sensor energy and data quality management of CPS. A major one that drives our work involves the large-scale management of heterogeneous devices that are expected to populate CPS systems. A great many sensor types, manufacturers, protocols, etc., are expected to co-exist and hence, any solution must be designed to operate as expected regardless of the device configuration. Regarding energy management, this motivates the need for a universal management approach that attempts to control MAC (medium access control) level energy consumption of nodes, as motivated by previous research [153]. Furthermore, an efficient management scheme should minimize the transmission of control messages crossing different domains, and thus we are seeking a long-term optimal solution. In regard to data quality management, a universal measure of expression can be found in recent work in quality-of-information (QoI) management. Broadly speaking, QoI relates to the ability to judge whether information is fit-for-use for a particular purpose [154, 155, 156]. For the purposes of this chapter, we will assume that QoI is characterized by a number of attributes including accuracy, latency, and physical context (specifically, sensor coverage in this chapter [154]).
AB - The previous three chapters address different aspects of the architectures of CPS. However, there are various technical challenges in sensor energy and data quality management of CPS. A major one that drives our work involves the large-scale management of heterogeneous devices that are expected to populate CPS systems. A great many sensor types, manufacturers, protocols, etc., are expected to co-exist and hence, any solution must be designed to operate as expected regardless of the device configuration. Regarding energy management, this motivates the need for a universal management approach that attempts to control MAC (medium access control) level energy consumption of nodes, as motivated by previous research [153]. Furthermore, an efficient management scheme should minimize the transmission of control messages crossing different domains, and thus we are seeking a long-term optimal solution. In regard to data quality management, a universal measure of expression can be found in recent work in quality-of-information (QoI) management. Broadly speaking, QoI relates to the ability to judge whether information is fit-for-use for a particular purpose [154, 155, 156]. For the purposes of this chapter, we will assume that QoI is characterized by a number of attributes including accuracy, latency, and physical context (specifically, sensor coverage in this chapter [154]).
UR - http://www.scopus.com/inward/record.url?scp=85053958337&partnerID=8YFLogxK
U2 - 10.1201/b19003
DO - 10.1201/b19003
M3 - Chapter
AN - SCOPUS:85053958337
SN - 9781482208979
SP - 101
EP - 130
BT - Cyber Physical Systems
PB - CRC Press
ER -