Conceptualizing and Programming Hybrid Services in the Cloud

Abstract

For solving complex problems, in many cases, software alone might not be sufficient and we need hybrid systems of software and humans in which humans not only direct the software performance but also perform computing and vice versa. Therefore, we advocate constructing "social computers" which combine software and human services. However, to date, human capabilities cannot be easily programmed into complex applications in a similar way like software capabilities. There is a lack of techniques to conceptualize and program human and software capabilities in a unified way. In this paper, we explore a new way to virtualize, provision and program human capabilities using cloud computing concepts and service delivery models. We propose novel methods for conceptualizing and modeling clouds of human-based services (HBS) and combine HBS with software-based services (SBS) to establish clouds of hybrid services. In our model, we present common APIs, similar to well-developed APIs for software services, to access individual and team-based compute units in clouds of HBS. Based on that, we propose a framework for utilizing SBS and HBS to solve complex problems. We present several programming primitives for hybrid services, also covering forming hybrid solutions consisting of software and humans. We illustrate our concepts via some examples of using our cloud APIs and existing cloud APIs for software.

Context-Aware Programming for Hybrid and Diversity-Aware Collective Adaptive Systems

“…Based on that, via software-defined APIs, we can create, provision and control HDA-CASs to enable units within these HDA-CASs to interact and perform their tasks/roles. Let us consider the case in which a HDA-CAS is built by using a hybrid compute unit (HCU) [6,7]. There are complex relationships among the What and Who/Which within a context and among contexts within the lifetime of a HDA-CAS, as shown in Fig.…”

“…Thus, initially the h 2 CAS can be just enough for solving a sub-graph and then eventually be extended to solve other tasks, e.g. followed the strategies in [6]. Although tasks are dependent, communications among h 2 CAS units performing tasks may or may not be established.…”

“…Since HDA-CASs are designed to deal with complex problems in an adaptive way, examining elasticity mechanisms for building HDA-CASs using cloud resources, offering cloud computing models for HDA-CASs, and dynamically managing HDA-CASs at runtime is a very interesting but challenging problem. In our previous work, we have described cloud models for software and people, basic hybrid compute unit models for establishing computing systems including both software and people, and basic programming APIs for these units [6,7]. In this paper, we examine how such fundamental building blocks can be used to build HDA-CASs.…”

Principles of Software-Defined Elastic Systems for Big Data Analytics

“…The next situation in our case study is that the result from Operation Data Analytics might need to be examined by people or the result from Machine/Human Event Analyzers signaling different critical situations (Critical Situations 1 & 2). Hence we invoke elasticity control to form units of human-based services and configure them in the right structure [14]. The question is how to provision such units and control the quality of their work.…”

“…The question is how to provision such units and control the quality of their work. Our approach aims at supporting diverse forms of humanbased compute units, which can be social compute units (SCU), crowds or hybrid compute units [14]. Furthermore, there is a need to coordinate the activities within computing units and among them.…”