Tight integration between classical and quantum networking requires strict synchronization of events between the classical and quantum portions of the network. Time-Sensitive Networking (TSN) as defined by IEEE 802.1Q is limited to accuracy on the order of microseconds due to limitations in time synchronization performance; TSN gate control is thus similarly limited. This work presents a new High-Precision TSN that enables greater accuracy and resolution toward sub-nanosecond TSN gate control and can directly support entanglement distribution, a key component in a software-designed quantum network architecture where classical control can reach deep into the quantum network and directly control time critical operations.

Although the importance of innovation and standardization (I&S) of technology is well understood in the information and communications technology (ICT) community, there is a lack of awareness of the definitions of I&S, the relationship between I&S, and popular theories of I&S. The IEEE Communications Society's Emerging Technical Subcommittee on Innovations and Standards in Information and Communication Technology (ISICT) recently conducted a survey that captures the current state of awareness of I&S theories in the ICT community. The survey is intended to help understand the problems that hinder popular adoption of I&S theories in mainstream industry and academic research processes. This paper analyzes the results of the survey to achieve two goals, namely, to quantify the problems and challenges encountered in understanding and studying I&S in ICT and to identify potential solutions to address the problems.

The communication network supports applications within the power grid that cannot be handled by local control; there is a mutual relationship that influences their network structures. This leads to the hypothesis that there is a fundamental relationship involving the eigenvalues of the power grid and communication network adjacency matrices. The intuitive relationship is that the communication network adjacency matrix should have stronger connectivity among nodes that are weakly connected in the power network adjacency matrix. The focus is upon latency rather than bandwidth since, in the application of fault detection, isolation, and recovery, messages are relatively small but their speed of transmission is of greater importance.

This paper explores the significance of persistence length in modeling and simulation of nanoscale networks. Persistence length, used by chemists and biologists, pertains to a wide range of high-aspect ratio, small-scale materials, and has a significant impact on communication at the nanoscale. For example, it applies to carbon nanotubes, microtubules, DNA, and nanowires as well as many other potential nanoscale network structures. Consider the similarities between microtubules in living cells and carbon nanotubes (CNTs). Both microtubules and carbon nanotubes have similar geometric structures and share similar properties; both are capable of transporting information at the nanoscale. Microtubules and carbon nanotubes can also self-organize to create random graph structures, which can be used as communication networks. At the same time, networks of CNTs may be used for molecular-level transport in the human body supporting treatment of diseases. This paper examines fundamental properties of network topologies created by filamentous structures and their relationship to the performance of nanoscale communication networks. This behavior depends strongly on the alignment of bond segments and filaments, which in turn depends on the persistence length of the tubes. We use graph spectral analysis for analyzing a simulated generic network of filamentous structures. A network graph is extracted from the layout of such a structure and graph properties of the resultant graph are examined. The paper presents the results of the simulation with tubes of different persistence lengths and makes the case for including persistence length as a parameter in standards for nanoscale communications. Our simulation results show that at different persistence lengths the network structure and the resultant properties of the graph structure that impact nanoscale communications can be predicted and analyzed. Such standard parameters help in calibrating an analytical model to a physical network allowing for synchronization between analytical and experimental results.

In this paper we present a biological Nano and MEMS communication platform that uses Nano logic computation based on controlled cell-signaling mechanisms. The proposed solution also integrates compartmentalisation techniques to support parallel processing. Based on our solution, our objective is to create a nanoscale communication networks between various biological Nano and MEMS devices within a tissue to support various medical applications (e.g. patient monitoring).

Mobile communication devices of the next generation are expected to have an increasingly diminishing form-factor and at the same time are expected to be capable of universal network access.Nanoscale networks [1] and molecular networking are on the horizon.This leads to numerous challenges due to limited resources, such as battery power, radio size, and limited transmission range.To obtain universal connectivity, such devices must be able to recognize and connect to networks in their vicinity by forming ad hoc networks until data reaches a backbone network.This should be accomplished instantaneously and seamlessly with or without the support of a preexisting infrastructure.These devices should have the capability for self-organization, support for multiple levels of quality of service, and high security.This special issue contains contributions in the area of wireless and ad hoc networking with special emphasis on resource-constrained communication devices.The networking community is slowly applying concepts from other disciplines in terms of selforganization and low-overhead, low-power networking, for example, techniques from biology such as using pheromones for route discovery in AntNet [2], stigmergic data fusion in sensor networks [3].Similarly, concepts from physics such as 1/f noise and power-law indicators of organization have been leveraged, e.g.cooperative energy savings [4], Boolean Networks and attractors [5], and self-organized clustering [6].However, there is still a long way to go.This issue begins with one of the best overview papers to have come out recently on this topic, by Kevin Mills, A Survey of Self-Organization in Wireless Networks.This paper surveys deeper theoretical aspects explaining how self-organization might be applied in tomorrow's wireless networks.It squarely

The primary contribution of this work is to examine the energy efficiency of pulse coupled oscillation for time synchronization in a realistic wireless network environment and to explore the impact of mobility on convergence rate. Energy coupled oscillation is susceptible to interference; this approach uses reception and decoding of short packet bursts to eliminate this problem. The energy efficiency of a commonly used timestamp broadcast algorithm is compared and contrasted with pulse-coupled oscillation. The emergent pulse coupled oscillation technique shows greater energy efficiency as well as robustness with mobility. The algorithm specifically includes the likelihood that some proportion of the sensors may include GPS receivers in order to obtain and propagate a master clock time.

This paper examines flexibility in ad hoc networks and suggests that, even with cross-layer design as a mechanism to improve adaptation, a fundamental limitation exists in the ability of a single optimization function, defined a priori, to adapt the network to meet all quality-of-service requirements. Thus, code implementing multiple algorithms will have to be positioned within the network. Active networking and programmable networking enable unprecedented autonomy and flexibility for ad hoc communication networks. However, in order to best leverage the results of active and programmable networking, metrics that indicate the nature and location of required flexibility need to be developed. The primary contribution of this paper is to propose a metric that couples network topological rate of change with the ability of a generic service to move itself to an optimal location in concert with the changing network. This metric points to a fundamental tradeoff among adaptation (changing service location), performance (sophistication or estimated minimum code size of the service), and the network's ability to tune itself to a changing ad hoc network topology.

If current trends continue, the next generation of enterprise networks is likely to become a more complex mixture of hardware, communication media, architectures, protocols, and standards. One approach toward reducing the management burden caused by growing complexity is to integrate management support into the inherent function of network operation. In this paper, management support is provided in the form of network components that, simultaneously with their network function, collaboratively project and adjust projections of future state based upon actual network state. It is well known that more accurate predictions over a longer time horizon enables better control decisions. This paper focuses upon improving prediction; the many potential uses of predictive capabilities for predictive network control will be addressed in future work.