Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze [1]. Big data is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors, and mobile devices transmit it. Big data is arriving from multiple sources at an alarming velocity, volume, and variety. To extract meaningful value from big data, you need optimal processing power, analytics capabilities, and skills [2]. Big data sets can usually be broken into four dimensions: volume, variety, velocity, and veracity. Because of the new characteristics of big data, new platforms and frameworks are required for big data management and data analytics. Cloud computing, often referred to as simply ‘the cloud’, is the delivery of on-demand computing resources—everything from applications to data centers—over the Internet on a pay-for-use basis [3]. Cloud computing also promises to accommodate a huge volume of data that is regarded as a promising methodology to deal with efficient big data processing. Integration of cloud and big data ecosystems thereby not only allows improved cloud resource utilization and efficiency but also brings optimized performance for big data applications underpinned by cloud infrastructures. Based on the trend that cloud infrastructures of traditional way in which big data applications are executed are undergoing radical change, cloud has evolved in many aspects including cloud architectures, cloud applications, cloud security, and cloud services. However, there are still many other challenges to be resolved to offer better support for big data applications. Research advances in big data and cloud computing continue to be major focus areas in research and industry and we expect that to continue for the next few years. This special issue focuses on new strategic research area that addresses ‘Recent Research Advances in Cloud Computing and Big Data’. From the submitted papers for the 2nd International IBM Cloud Academy Conference (ICA CON 2014) held in Atlanta, GA, USA, on May 8–9, 2014 and the Second International Conference on Advanced Cloud and Big Data (CBD 2014) held in Huangshan, Anhui, China, on November 20–22, 2014, eight papers are selected that target the following research issues in big data and cloud computing:
[1]
Lijuan Wang,et al.
Bio‐inspired cost‐aware optimization for data‐intensive service provision
,
2015,
Concurr. Comput. Pract. Exp..
[2]
J. Manyika.
Big data: The next frontier for innovation, competition, and productivity
,
2011
.
[3]
Wei Zheng,et al.
An adaptive deadline constrained energy‐efficient scheduling heuristic for workflows in clouds
,
2015,
Concurr. Comput. Pract. Exp..
[4]
Ming Yang,et al.
A novel application classification attack against Tor
,
2015,
Concurr. Comput. Pract. Exp..
[5]
Bin Li,et al.
SGAM: strategy‐proof group buying‐based auction mechanism for virtual machine allocation in clouds
,
2015,
Concurr. Comput. Pract. Exp..
[6]
Fang Dong,et al.
Entropy-Based Denial of Service Attack Detection in Cloud Data Center
,
2014,
2014 Second International Conference on Advanced Cloud and Big Data.
[7]
Fang Dong,et al.
Towards optimized scheduling for data‐intensive scientific workflow in multiple datacenter environment
,
2015,
Concurr. Comput. Pract. Exp..
[8]
Mahmoud Al-Ayyoub,et al.
Evaluating map reduce tasks scheduling algorithms over cloud computing infrastructure
,
2015,
Concurr. Comput. Pract. Exp..
[9]
Grzegorz Kolaczek,et al.
Trust‐based security‐level evaluation method for dynamic service‐oriented environments
,
2015,
Concurr. Comput. Pract. Exp..