This thesis introduces QSMA-CR, a MAC layer protocol that leverages carrier sensing to achieve lower latency than its predecessors: QSMA and ALOHA-QS. QSMA-CR establishes a distributed queue to maintain fairness and achieve high throughput. Each node sends data frames within their reserved slot every queue cycle. After every cycle is a joining period in which unjoined nodes attempt to make a reservation. In QSMA and ALOHA-QS, nodes have latency due to a lack of a contention resolution algorithm that optimizes the join process. QSMA-CR has a global and node-level state, enabling smarter contention resolution that allows high throughput and lower latency. We used a 10-minute experiment with 50 nodes to show that QSMA-CR can achieve lower latency than QSMA achieving similar throughput.

Computer networks are complex constructs consisting of many entities that simultaneously interact with one another. Understanding various aspects of such complex systems and their scaling properties is therefore a challenging task. This thesis studies the performance of computer networks through several layers of abstraction—namely communication, social and information—and investigates the interplay between these layers at a large scale and from an analytical point of view. The results derived from this analysis are crucial in early identifying of design issues and potential weaknesses of large-scale networks such as the Internet for which performing simulations is prohibitive.

The first part of this dissertation studies how the spatial diversity of social contacts affect the scalability of communication networks and identifies classes of social models that let computer networks properly scale. From this analysis, it is established that scalability is achieved under social models in which social contacts are statistically concentrated within a confined geographical region around each node. We shall recognize that the true distribution of social contacts in real networks does not generally meet this requirement, imposing a scalability gap on today's networks.

The second part of the dissertation studies information-centric networking (ICN); a framework that utilizes distributed content caching that can be used to bridge the foregoing scalability gap. Three dominant methods of distributed content caching—namely uniform-, optimal- and edge-caching—are compared. We shall see that caching only at the edge of the network outperforms uniform-caching (the de facto standard of ICN) in terms of end-to-end latency while offering slightly inferior results compared to the more complex optimal-caching strategy. This result is further augmented by the observation that higher degrees of reference locality in space and/or time improve the performance of edge-caching, making it a viable alternative to optimal solution.

Finally, an analysis of the forwarding plane of ICN is presented. In the absence of host addressing, ICN routers are required to keep track of all requests (Interests) passing through them in Pending Interest Tables (PITs) that are needed to deliver data back to the requesters as well as to enable optimization mechanisms such as Interest aggregation. Through careful analysis of the PIT size distribution and the probability of Interest aggregation at PIT, we shall see not only are the true benefits from the stateful forwarding plane of ICN much smaller than anticipated, but also they come at the high expense of maintaining very large PITs. These results reveal that the forwarding plane of ICN must be rethought; an important finding that provokes the investigation of a stateless forwarding plane for future ICNs.

The current Internet architecture was designed at the 1960s and 70s, to address communication needs of that time: sharing limited, expensive, and static computer resources. Since then, the Internet usage pattern has been shifted from conventional host-centric model to a flexible content-oriented model, in which users and contents are distributed and mobile. Internet of Things is becoming a new paradigm to describe global access to services and information offered by billions of heterogeneous devices, "things", ranging from resource-constrained to powerful devices in an interoperable way.

The first part of this dissertation studies the routing in Information-Centric Networks (ICN). ICN has been recently proposed and is inspiring the design of the future Internet architecture. The goal in these architectures is to provide a cost-efficient, scalable and mobile content distribution networking by adopting a content-based model of communication. ICN not only addresses the change in the Internet usage pattern but also matches the IoT applications, since they target data regardless of the identity of the object that stores or originates them.

In this dissertation, Named-data network (NDN) and Content-Centric Networking (CCNx) are presented and routing strategies for them are evaluated. A comprehensive performance evaluation is done through the simulation experiments. We enhanced the performance of link-state routing by introducing a new protocol called LSCR, link-state content routing protocol, a loop-free name-based routing algorithm that propagates link-state information selectively and provides multi-path routing to content that may be replicated in different locations. We also introduced the first content routing protocol based on the diffusing computation, DNRP. DNRP provides multiple loop-free routes to the nearest instances of a data using only distance information and without requiring periodic updates, knowledge of the network topology, or the exchange of path information.

MANET paves the way for the development of brand new IoT communication platforms with a high potential for a wide range of applications in different domains. Each layer in the design model require redefinition or modifications to function efficiently in MANETs every is mobile and usually has limited resources on computation, storage, power, etc.

Routing in Mobile Ad-Hoc Networks is studied in the second part of this dissertation. We introduce ODVR (Ordered Distance Vector Routing), that provides loop-free routes at every instant based solely on distances to destinations maintained by nodes and reference distances included in route requests. Routing state is established on demand by means of route requests stating the reference distance and replies from nodes that satisfy this distance. To make the routing more efficient in an IoT environment with a base or gateway nodes, we introduce ADRP, a hybrid routing algorithm that takes advantage of the strengths of reactive routing algorithms as well as the benefits of proactive ones. ADRP uses the same signaling for both reactive and proactive routing.