We propose a new approach for developing and deploying distributed systems, in which
nodes predict distributed consequences of their actions and use this information to detect …

This paper introduces the concept of monitoring-as-a-service (MaaS), its main components,
and a suite of key functional requirements of MaaS in cloud. We argue that MaaS should …

Federated stream processing systems, which utilise nodes from multiple independent
domains, can be found increasingly in multi-provider cloud deployments, internet-of-things …

Several complex event processing (CEP) middleware solutions have been proposed in the
past. They act by processing primitive events generated by sources, extracting new …

Information quality (IQ) is a measure of how fit information is for a purpose. Sometimes
called Quality of Information (QoI) by analogy with Quality of Service (QoS), it quantifies …

Fault tolerance is critical for distributed stream processing systems, yet achieving error-free
fault tolerance often incurs substantial performance overhead. We present AF-Stream, a …

State monitoring is widely used for detecting critical events and abnormalities of distributed
systems. As the scale of such systems grows and the degree of workload consolidation …

In the emerging cloud computing era, enterprise data centers host a plethora of web
services and applications, including those for e-Commerce, distributed multimedia, and …

Monitoring global states of a distributed cloud application is a critical functionality for cloud
datacenter management. State monitoring requires meeting two demanding objectives: high …

We present LiMoSense, a fault-tolerant live monitoring algorithm for dynamic sensor
networks. This is the first asynchronous robust average aggregation algorithm that performs …