You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Multimedia Internet of Things: A Comprehensive Survey 
Chapter Title:  D. FOG/EDGE COMPUTING 
1. Abstract of Cited Paper (BIB001):  Fog computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage and application services to end users. In this article, we elaborate the motivation and advantages of Fog computing and analyse its applications in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks. We discuss the state of the art of Fog computing and similar work under the same umbrella. Distinguished from other reviewing work of Fog computing, this paper further discloses the security and privacy issues according to current Fog computing paradigm. As an example, we study a typical attack, man-in-the-middle attack, for the discussion of system security in Fog computing. We investigate the stealthy features of this attack by examining its CPU and memory consumption on Fog device. In addition, we discuss the authentication and authorization techniques that can be used in Fog computing. An example of authentication techniques is introduced to address the security scenario where the connection between Fog and Cloud is fragile. Copyright © 2015John Wiley & Sons, Ltd. 
2. Abstract of Cited Paper (BIB002):  The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.

Literature Review:
For decades cloud computing served as pay-as-you-go, managing and providing alternative solutions for data centers and enterprises by providing remote storage units, processing units, networks, servers and applications to serve multiple customers BIB001 . Cloud computing flows a centralized processing infrastructure which is usually located far from users or IoT proximity. However, cloud computing upsurges network overheads by transmitting the aggregated data from sensors to the centralized processing cloud and then acquiring back the analyzed data over bandwidth, latency, and energyconstrained network. M-IoT network requires a model that can handle high velocity, volume, and variety of data with minimum latency, conserve bandwidth, reliability, globally secure and chooses the best processing unit in the least possible time. In 2012, Cisco introduced and defined fog computing as  : ''The fog extends the cloud closer to the things that produce and act on IoT data.'' Fog computing is the virtualized platform that offers computation, storage units and routing devices between User Equipment (UE) and traditional cloud, located at the edge of the network, reducing the response time of the system  . The fog-cloud hybrid computing architecture process the data in the following pattern. Critical time-sensitive and real-time data are processed on the fog node, while less critical data that can tolerate minute delay is processed and stored on fog gateway node for a few hours. The regular periodic data that is not delay-sensitive is sent to the cloud to be processed and stored for offline access  . Stojmenovic et al. BIB002 outlined a detailed overview of fog computation applications and challenges. The term edge computing also refers to the notion of providing computation at the edge of the network. The edge computing is defined as network processing and resources progressing between data origin and cloud unit BIB003 . Detailed edge computing architecture and issues are presented in BIB003 . The smartphone act as an edge between the user and the cloud. The processing unit is placed within the proximity of data producers to increase energy efficiency, response time, and bandwidth allocation optimization. Fog computing is referred to as edge computing. However, the difference lies in the location of the computing unit is placed. Fog computing is employed at the Local Area Network (LAN) or the gateways of the network, whereas edge computing is embedded within the end or edge device, as shown in Fig. 13 . Linthicum et al. describe edge computing as the concept, while fog computing as a protocol to implement edge computing [204] . The authors also highlighted the limitations of both the architectures in data computing. Various fog and edge computing frameworks, vision, and challenges in the M-IoT network are studied and presented in the subsection.