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:  1) MULTIMEDIA COMPUTING IN SDN 
1. Abstract of Cited Paper (BIB001):  A novel paradigm that changes the scene for the modern communication and computation systems is the Edge Computing. It is not a coincidence that terms like Mobile Cloud Computing, Cloudlets, Fog Computing, and Mobile-Edge Computing are gaining popularity both in academia and industry. In this paper, we embrace all these terms under the umbrella concept of “Edge Computing” to name the trend where computational infrastructures hence the services themselves are getting closer to the end user. However, we observe that bringing computational infrastructures to the proximity of the user does not magically solve all technical challenges. Moreover, it creates complexities of its own when not carefully handled. In this paper, these challenges are discussed in depth and categorically analyzed. As a solution direction, we propose that another major trend in networking, namely software-defined networking (SDN), should be taken into account. SDN, which is not proposed specifically for Edge Computing, can in fact serve as an enabler to lower the complexity barriers involved and let the real potential of Edge Computing be achieved. To fully demonstrate our ideas, initially, we put forward a clear collaboration model for the SDN-Edge Computing interaction through practical architectures and show that SDN related mechanisms can feasibly operate within the Edge Computing infrastructures. Then, we provide a detailed survey of the approaches that comprise the Edge Computing domain. A comparative discussion elaborates on where these technologies meet as well as how they differ. Later, we discuss the capabilities of SDN and align them with the technical shortcomings of Edge Computing implementations. We thoroughly investigate the possible modes of operation and interaction between the aforementioned technologies in all directions and technically deduce a set of “Benefit Areas” which is discussed in detail. Lastly, as SDN is an evolving technology, we give the future directions for enhancing the SDN development so that it can take this collaboration to a further level. 
2. Abstract of Cited Paper (BIB002):  Abstract Recently, there has been an increasing interest in the Internet of Things (IoT). While some analysts disvalue the IoT hype, several technology leaders, governments, and researchers are putting serious efforts to develop solutions enabling wide IoT deployment. Thus, the huge amount of generated data, the high network scale, the security and privacy concerns, the new requirements in terms of QoS, and the heterogeneity in this ubiquitous network of networks make its implementation a very challenging task. SDN, a new networking paradigm, has revealed its usefulness in reducing the management complexities in today's networks. Additionally, SDN, having a global view of the network, has presented effective security solutions. On the other hand, fog computing, a new data service platform, consists of pushing the data to the network edge reducing the cost (in terms of bandwidth consumption and high latency) of “big data” transportation through the core network. In this paper, we critically review the SDN and fog computing-based solutions to overcome the IoT main challenges, highlighting their advantages, and exposing their weaknesses. Thus, we make recommendations at the end of this paper for the upcoming research work.

Literature Review:
SDNs are not specifically introduced for data computing. However, managing the network proficiently by SDNs could reduce the computing complexity to yield low latency and fewer overheads. Kaur et al. in [226] devised SDN as a middleware in edge-cloud hybrid architectures to improve the energy efficiency of the stream processing. The framework provides the classification of data flow into batch processing and stream processing. Batch processing is more focussed on network service bandwidth while stream processing comprehends real-time applications that are latency-sensitive. Upon the classification of workflow, network control logic are configured and implemented. The authors have formulated multi-objective optimization problems for each control logic, which exploits the Tchebycheff decomposition algorithm to solve the problems to minimize energy consumption by efficient routing path selection and scheduling. Results show that incorporating dynamic network changes according to the classified workflow enhances the energy efficiency meeting SLA. Salman et al. BIB001 proposed Software-Defined Mobile Edge Computing (SD-MEC) architecture to reduce latency and bandwidth by combining the features of both SDN and edge computing. The proposed framework offers scalability by managing the distributed edge network with SDN controllers to incorporate network changes and developing new services. Wang et al.  presented SDN-based-Publish/Subscribe (SDNPS) unified framework to serve multiple IoT applications. The presented framework aims to reduce the latency and throughput of the network with publishers that publish the generated data and offer services tagged with specific event topics to SDN. The subscribers that require specific event services receive their desired services from SDN based middleware without interaction with the publisher. SDNPS leads to a unified, interoperable framework. Baktir et al. BIB002 detailed the limitations and challenges of cloud-edge computing with increasing data traffic and proposed a vision of SDN based network management strategy to decrease the complexity of cloud-edge architectures. Authors have highlighted several use cases, including multimedia data computation in IoT for face detection and revealed the benefits of incorporating SDNs to add scalability and reliability in the network. A comprehensive survey and future research direction on SDN and fog computing is presented by Salman et al. BIB003 .