IEEE Communications Magazine • July 2017 172 SERIES EDITORIAL M obile applications and Internet of Things (IoT) plat- forms that utilize cloud computing technologies have become increasingly popular in recent years. The cloud provides data storage and processing capabilities that make it possible to run computation-intensive applications on devices with limited processing power. The cloud helps such devices do the “heavy lifting” when necessary. This design is challenged today by Internet delays and networking overheads. However, the cloud has a significant energy footprint and suf- fers from the drawbacks of extreme centralization [1]. Thus, we witness a return to a more traditional grid-like future, where resources from all over the world are fused together into the grid and commonly used for a greater goal. Instead of external- izing all the business to the cloud, the cloud is brought closer to the business through set-top box equipment and cloudlet con- structs, and we witness the rise of paradigms where processing of sensed data is done on machines running closer-than-cloud, whenever possible in the same network as the sensing machines themselves. An analysis of the work in this direction and a concrete decentralized proposal are presented in the first work, “EXEGE- SIS: Extreme Edge Resources Harvesting for a Virtualized Fog Environment.” In the article, the authors propose to harness unutilized resources at the edge of the cloud, via a three-layer architecture that encompasses the mist, fog, and cloud. The arti- cle leverages existing cloud architectures, enabling them to inter- act with this new edge-centric ecosystem of devices/resources, and benefit from the fact that critical data are available where they can add the most value. On the same topic of data collection, the second article, “Coordinate-Assisted Routing Approach to Bypass Routing Holes in Wireless Sensor Networks,” analyzes face-based geo- graphic routing in wireless sensor networks. The authors identify several issues with existing technology, and further propose a routing algorithm that solves the routing hole problem by using relative coordinate systems. With caching technologies, cloud data is accessed at lower latencies, because it is transferred closer to the destination thanks to content delivery networks. We have mobile networks spreading their operation services, with applications running at the edge of the network thanks to mobile edge computing (MEC). MEC proposes a novel network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular net- work [2]. By running applications and performing related pro- cessing tasks closer to the cellular customer, network congestion is reduced and applications perform better. The third article in this issue, “Crowd Associated Network: Exploiting over Smart Garbage Management System,” pres- ents an approach toward building future networks that will not rely on dense networking infrastructures — making the case for a crowd associated network (CAN). In such a network, a set of crowds complements possible communication gaps at infrastructure level, and authors demonstrate their concept for city-level implementation of a smart garbage management sys- tem (SGMS). The CAN is based on the MEC philosophy by employing a set of dedicated “agents” that run decision tasks for the operation of the network. The common denominator for many technology facelifts today is this: we want to bring data and processing closer to the devices that require it. Processing in the cloud, everyone agrees, will simply not be enough soon — for mobile and business apps, even a few seconds matter. Thus, we see today’s Internet moving from a network of computers to a dynamic network of networks, merging smart devices together with traditional computer networks. The current evolution is heading toward an increasingly interconnected, mobile, pervasive, and ubiquitous Internet of networks, which range from small wireless sensor networks to extended local area networks, all of them remotely accessible. However, all these paradigms are still based on the traditional client/server model: a (mobile/static) device sends a request for an operation, which is served back by a delegated provider. As the authors of the fourth article, “A Hitchhiker’s Guide to Computation Offloading: Opinions from Practitioners,” remark, we can glimpse a future where decentralization is seen as a complementary solution to today’s technology. Some of the communication could be made through device-to-device direct exchanges [3], relieving some of the throughput required of the cellular infrastructure. This is especially true for computation offloading [4] and remote execution for mobile devices. The authors of the fourth article make a thorough review of devel- opments on computation offloading and remote execution. They use their findings to provide designers with guidelines to gain a deep insight into the implementation challenges of a computa- tion offloading system. The authors demonstrate their findings through a pilot Android-based offloading system, evaluating it over two real-time applications. These articles provide some answers to questions about the continuing evolution of the field of wireless ad hoc networks, both in supporting different applications and in different technol- ogies used to solve specific issues. We thank all the reviewers and the editorial team for their work and their invaluable sup- port. REFERENCES [1] S. Giordano and D. Puccinelli, “The Human Element as the Key Enabler of Per- vasiveness,” Proc. 10th IFIP Annual Mediterranean Ad Hoc Networking Wksp. (Med-Hoc-Net), IEEE 2011. [2] Y. C. Hu et al., “Mobile Edge Computing — A Key Technology Towards 5G,” ETSI White Paper 11 (2015) [3] R.-C. Marin and C. Dobre, “Reaching for the Clouds: Contextually Enhancing Smartphones for Energy Efficiency,” Proc. 2nd ACM Wksp. High Performance Mobile Opportunistic Systems, 2013. [4] A. Ferrari et al. , “Reducing Your Local Footprint with Anyrun Computing,” Comp. Commun., Elsevier, 2016. Ad Hoc And SenSor networkS Silvia Giordano Ciprian Dobre Edoardo Biagioni