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Abstract-Broadcast has been traditionally regarded as a prohibitive communication transaction in multiprocessor environments. Nowadays, such constraint largely drives the design of architectures and algorithms all-pervasive in diverse computing domains, directly and indirectly leading to diminishing performance returns as we reach the manycore era. Novel interconnect technologies could allow to revert this trend by offering, among others, improved broadcast support even in large-scale chip multiprocessors. In this position paper, the prospects of wireless on-chip communication technologies pointing towards low-latency (a few cycles) and energy-eff cient (a few pJ/bit) broadcast are outlined. This work also discusses the challenges and potential impact of adopting these technologies as key enablers of unconventional hardware architectures and algorithmic approaches, in the pathway of signif cantly improving the performance, energy eff ciency, scalability and programmability of manycore chips.

Abstract-The Internet of Things (IoT) promises a plethora of new services and applications. To reach its potential IoT must break down the silos that limit applications' interoperability and hinder their manageability. Doing so leads to the building of Ultra-Large Scale Systems (ULSS) in several verticals, including Autonomous Vehicles, Smart Cities, and Smart Grids. The scope of ULSS is large in the number of things and complex in the variety of applications, volume of data, and diversity of communication patterns. To handle this scale and complexity we propose Hierarchical Emergent Behaviors (HEB), a paradigm that builds on the concepts of emergent behavior and hierarchical organization. Rather than explicitly programming all possible decisions in the vast space of ULSS scenarios, HEB relies on the emergent behaviors induced by local rules at each level of the hierarchy. In this paper we discuss the modifications to classical IoT architectures required by HEB, as well as the new challenges. We also illustrate the HEB concepts in reference to Autonomous Vehicles. This use case paves the way to the discussion of new lines of research.

The Internet of Things (IoT) marks a phase transition in the evolution of the Internet, distinguished by a massive connectivity and the interaction with the physical world. The organic evolution of IoT requires the consideration of three dimensions: scale, organization, and context. These dimensions are particularly relevant in Ultra Large Scale Systems (ULSS), of which Autonomous Vehicles is a prime example. Fog Computing is well positioned to support contextual awareness and communication, critical for ULSS. The design and orchestration of ULSS require fresh approaches, new organizing principles. A recent paper proposed HEB (Hierarchical Emergent Behaviors), an architecture that builds on established concepts of emergent behaviors and hierarchical decomposition and organization. HEB's local rules induce emergent behaviors, i.e., useful behaviors not explicitly programmed. In this chapter we take a first step to validate HEB concepts through the study of two basic self-driven car "primitives": exiting a platoon formation, and maneuvering in anticipation of obstacles beyond the range of on-board sensors. Fog nodes provide the critical contextual information required.