# Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser
## 2 Related Work  
The fog computing (FC) paradigm is promising in its ability to solve cloud-centric problems, especially in terms of latency and quality of service (QoS). Decreasing the latency of different cloud services is considered one of the main advantages of the FC paradigm. This advantage is inherited from the fog architecture (FA) itself. Various previous research efforts aimed to utilize FA to achieve optimal latency reduction. Most of these studies concerned moving computations to closer nodes in the fog stratum, referred to as computation offloading. In [4], a container-based framework was proposed to deploy microservices in the FA with minimal communication and computation costs. An application offloading strategy in the fog cloud architecture that used the accelerated particle swarm optimization technique was introduced in [5]. A collaborative offloading policy for fog nodes that attempted to minimize the IoT application delays was proposed and evaluated against a developed analytical model in [6]. A request offloading framework was proposed in [7], which employed a collaboration strategy among fog nodes to compute data in a shared mode. [PERSON] et al. [8] provided a comprehensive survey regarding all related research efforts in fog and edge computing. They classified these research efforts into nine categories: foundation, frameworks and programming models, design and planning, resource management, operation, software and tools, testbeds, security, and hardware and protocol stack. Our research is concerned about resource management and operations contributions. These contributions have failed to provide a general-purpose framework that uses FA in a tolerant, maintainable, and controllable manner. Most of them aimed to utilize the processing power available in the fog nodes by offloading the computations closer to the consumer. While this approach might move in the right direction in order to make use of these computation capabilities in the fog stratum, it still does not provide the standardization and the usability the industry needs. This is mainly due to the number of variations needed for every computation domain, and this affects the offloading strategies. Given that the number of static contents requested via networks represents a considerable percentage of each HTTP request (JS files, images, style sheets, plain texts, videos, etc. ), caching near the consumer is another approach to achieve reductions in latency for the consumer. Content delivery networks (CDNs) are defined by the Internet and Engineering Task Force (IETF) RFC 3466 [9] as a type of network in which servers and contents are arranged in an effective manner with respect to clients. In CDNs, cache servers, also called surrogate servers, which have a copy of the main service contents, are geographically distributed around the world. This enables cloud providers to fulfill end user requests in a faster manner by relying on the nearest cache server. Figure 1 represents an abstract architecture of CDNs where cloud data centers have their own server instances in other geographic locations. The consumer represented as IoT device, PC, or laptop gets their request satisfied from the nearest servers. Expansion of the network architecture in Figure 1 to show the fog stratum is shown in Figure 2. As shown, the fog stratum can be perceived as a multi-tier network architecture. Between the end consumer and the cloud services, the requests travel through multiple different networks in which these networks have computing and storage capabilities. The devices with computing and storage capabilities are called fog nodes (FNs). Figure 1: CDN abstract architecture. Utilizing FNs in a CDN model is a promising method of reducing latencies in web services. In [10], a caching mechanism (Semi-Edge) was proposed, in which they used in-network caching to achieve latency reduction. The Information Centric Networking (ICN) approach was proposed in [11] to achieve a fog-based CDN.