Biblio

Voting among replicated data collection devices is a means to achieve dependable data delivery to the end-user in a hostile environment. Failures may occur during the data collection process: such as data corruptions by malicious devices and security/bandwidth attacks on data paths. For a voting system, how often a correct data is delivered to the user in a timely manner and with low overhead depicts the QoS. Prior works have focused on algorithm correctness issues and performance engineering of the voting protocol mechanisms. In this paper, we study the methods for autonomic management of device replication in the voting system to deal with situations where the available network bandwidth fluctuates, the fault parameters change unpredictably, and the devices have battery energy constraints. We treat the voting system as a `black-box' with programmable I/O behaviors. A management module exercises a macroscopic control of the voting box with situational inputs: such as application priorities, network resources, battery energy, and external threat levels.
 

Voting among replicated data collection devices is a means to achieve dependable data delivery to the end-user in a hostile environment. Failures may occur during the data collection process: such as data corruptions by malicious devices and security/bandwidth attacks on data paths. For a voting system, how often a correct data is delivered to the user in a timely manner and with low overhead depicts the QoS. Prior works have focused on algorithm correctness issues and performance engineering of the voting protocol mechanisms. In this paper, we study the methods for autonomic management of device replication in the voting system to deal with situations where the available network bandwidth fluctuates, the fault parameters change unpredictably, and the devices have battery energy constraints. We treat the voting system as a `black-box' with programmable I/O behaviors. A management module exercises a macroscopic control of the voting box with situational inputs: such as application priorities, network resources, battery energy, and external threat levels.