The design and evolution of communication systems have mainly been driven by a maximalist approach to date. Such an approach sets audacious, often hard-to-achieve goals and comes with inflated requirements in terms of resources, network over-provisioning, and ineffective scalability. However, communication systems are currently evolving to cater to emerging cyber-physical systems with real-time interactive and networked sensing and (monitoring) actuation agents for use cases such as swarm robotics, self-driving cars, and smart Internet of Things (IoT) ecosystems. Accordingly, a fundamental shift in thinking is necessary to satisfy the pressing requirements for timely multimodal communication, autonomous decision-making, and efficient distributed processing. In this context, goal-oriented semantic communication could be viewed as a minimalist design approach based on the principle of “less is more.” This approach advocates for a paradigm shift from extreme to sustainable performance, emphasizing the importance of effective information exchange aligned with specific goals.
According to the literature, the effectiveness problem in communication systems has been studied within the goal-oriented semantic communication framework, where the objective is to maximize communication effectiveness while significantly improving network resource usage, energy consumption, and computational efficiency. Goal-oriented effectiveness deals with whether a message communicated within a system results in a desirable effect or the right impact at its destination to accomplish a specific goal. Specifically, in status update systems, an effectiveness-empowered approach entails that a sensing agent generates and communicates a status update packet only if it has the potential to provide such an effect or impact at the (destination) endpoint. This impact might involve enabling an actuation agent to carry out a critical action or alerting a monitoring agent to an emergency. Adopting the concept of goal-oriented effectiveness could enhance system scalability and promote efficient resource utilization by preventing the acquisition, processing, and transmission of information that may ultimately prove ineffective, irrelevant, or unnecessary. Therefore, it has the potential to make various network processes more efficient and effective, allowing for a parsimonious use of communication and computation resources.
Historically, the goal-oriented semantic communication paradigm represents a timely research venue for realizing the long-standing vision of Shannon and Weaver by incorporating the goal-oriented effectiveness of information exchange into the existing theoretical framework. Earlier contributions to this field explored the foundational idea of partitioning communication problems into three levels: effectiveness, semantics, and technical implementation. Nevertheless, most of the efforts in the literature remained conceptual, leading to hardly any or no practically relevant applications. Within recent years, the pursuit of such a theory has gained renewed momentum. This resurgence has been driven by the advent of networked intelligent systems, real-time cyber-physical systems, and autonomous networks, which demand advanced communication paradigms to meet their evolving requirements. Subsequently, further efforts have been devoted to integrating the goal-oriented semantic communication paradigm into the existing theoretical framework, aiming to bridge the gap between conceptual insights and development from different viewpoints.
Semantics-aware fault detection in Internet of Things (IoT) systems and the role of semantic communication in reducing the age of incorrect information (AoII) highlight the paradigm’s relevance in time-sensitive scenarios. Scheduling strategies that focus on the value of information (VoI) and peak-to-average power ratio considerations in semantic communication systems further underscore its potential for efficient resource management. Additionally, research has introduced task-oriented communication frameworks, data significance-driven approaches in networked systems, and fidelity-based methodologies for goal-oriented semantic communication. Further advancements include strategies for trajectory estimation, bidirectional wireless links, and sensor reporting for non-linear dynamic systems. These developments culminate in integrated approaches such as the 6G-GOALS framework, showcasing the paradigm’s capacity to enable adaptive, intelligent, and effective communication systems in next-generation networks.
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