Add to ORKGAbstract. This paper describes the SODA scheduler for System S, a highly scalable distributed stream processing system. Unlike traditional batch applications, streaming applications are open-ended. The system cannot typically delay the processing of the data. The scheduler must be able to shift resource allocation dynamically in response to changes to resource availability, job arrivals and departures, incoming data rates and so on. The design assumptions of System S, in particular, pose ad-ditional scheduling challenges. SODA must deal with a highly complex optimization problem, which must be solved in real-time while main-taining scalability. SODA relies on a careful problem decomposition, and intelligent use of both heuristic and exact a...
The era of big data has led to the emergence of new systems for real-time distributed stream process...
Task scheduling in distributed stream computing systems is an NP-complete problem. Current schedulin...
Distributed Stream Processing Systems (DSPS) are ``Fast Data'' platforms that allow streaming applic...
Abstract. This paper describes the SODA scheduler for System S, a highly scalable distributed stream...
Abstract. This paper describes the SODA scheduler for System S, a highly scalable distributed stream...
This paper describes the SODA scheduler for System S, a highly scalable distributed stream processin...
Abstract. This paper describes a new and novel scheme for job admission and resource allocation empl...
This paper describes a new and novel scheme for job admission and resource allocation employed by th...
Data streaming applications in Cyber-Physical Systems enable high-throughput, low-latency transforma...
In this study, we investigated the problem of scheduling streaming applications on a heterogeneous c...
Stream processing systems receive continuous streams of messages with raw information and produce s...
ii The era of big data has led to the emergence of new systems for real-time distributed stream proc...
In the era of big data, with streaming applications such as social media, surveillance monitoring an...
Data streaming applications in Cyber-Physical Systems enable high-throughput, low-latency transforma...
The velocity dimension of Big Data refers to the need to rapidly process data that arrives continuou...
The era of big data has led to the emergence of new systems for real-time distributed stream process...
Task scheduling in distributed stream computing systems is an NP-complete problem. Current schedulin...
Distributed Stream Processing Systems (DSPS) are ``Fast Data'' platforms that allow streaming applic...
Abstract. This paper describes the SODA scheduler for System S, a highly scalable distributed stream...
Abstract. This paper describes the SODA scheduler for System S, a highly scalable distributed stream...
This paper describes the SODA scheduler for System S, a highly scalable distributed stream processin...
Abstract. This paper describes a new and novel scheme for job admission and resource allocation empl...
This paper describes a new and novel scheme for job admission and resource allocation employed by th...
Data streaming applications in Cyber-Physical Systems enable high-throughput, low-latency transforma...
In this study, we investigated the problem of scheduling streaming applications on a heterogeneous c...
Stream processing systems receive continuous streams of messages with raw information and produce s...
ii The era of big data has led to the emergence of new systems for real-time distributed stream proc...
In the era of big data, with streaming applications such as social media, surveillance monitoring an...
Data streaming applications in Cyber-Physical Systems enable high-throughput, low-latency transforma...
The velocity dimension of Big Data refers to the need to rapidly process data that arrives continuou...
The era of big data has led to the emergence of new systems for real-time distributed stream process...
Task scheduling in distributed stream computing systems is an NP-complete problem. Current schedulin...
Distributed Stream Processing Systems (DSPS) are ``Fast Data'' platforms that allow streaming applic...