Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals

We consider a wireless network with a base station serving multiple traffic streams to different destinations. Packets from each stream arrive to the base station according to a stochastic process and are enqueued in a separate (per stream) queue. The queueing discipline controls which packet within each queue is available for transmission. The base station decides, at every time t, which stream to serve to the corresponding destination. The goal of scheduling decisions is to keep the information at the destinations fresh. Information freshness is captured by the Age of Information (AoI) metric. In this paper, we derive a lower bound on the AoI performance achievable by any given network operating under any queueing discipline. Then, we consider three common queueing disciplines and develop both an Optimal Stationary Randomized policy and a Max-Weight policy under each discipline. Our approach allows us to evaluate the combined impact of the stochastic arrivals, queueing discipline and scheduling policy on AoI. We evaluate the AoI performance both analytically and using simulations. Numerical results show that the performance of the Max-Weight policy is close to the analytical lower bound

Age of Information in Multi-Hop Status Update Systems: Fundamental Bounds and Scheduling Policy Design

Freshness of information has become of high importance with the emergence of many real- time applications like monitoring systems and communication networks. The main idea behind all of these scenarios is the same, there exists at least a monitor of some process to which the monitor does not have direct access. Rather, the monitor indirectly receives updates over time from a source that can observe the process directly. The common main goal in these scenarios is to guarantee that the updates at the monitor side are as fresh as possible. However, due to the contention among the nodes in the network over limited channel resources, it takes some random time for the updates before they are received by the monitor. These applications have motivated a line of research studying the Age of Information (AoI) as a new performance metric that captures timeliness of information. The first part of this dissertation focuses on the AoI problem in general multi-source multi-hop status update networks with slotted transmissions. Fundamental lower bounds on the instantaneous peak and average AoI are derived under general interference constraints. Explicit algorithms are developed that generate scheduling policies for status update dissem- ination throughout the network for the class of minimum-length periodic schedules under global interference constraints.\nNext, we study AoI in multi-access channels, where a number of sources share the same server with exponentially distributed service times to communicate to a monitor. Two cases depending on the status update arrival rates at the sources are considered: (i) random arrivals based on the Poisson point process, and (ii) active arrivals where each source can generate an update at any point in time. For each case, closed-form expressions are derived for the average AoI as a function of the system parameters.\nNext, the effect of energy harvesting on the age is considered in a single-source single- monitor status update system that has a server with a finite battery capacity. Depending on the server’s ability to harvest energy while a packet is in service, and allowing or blocking the newly-arriving packets to preempt a packet in service, average AoI expressions are derived. The results show that preemption of the packets in service is sub-optimal when the energy arrival rate is lower than the status update arrival rate.\nFinally, the age of channel state information (CSI) is studied in fully-connected wire- less networks with time-slotted transmissions and time-varying channels. A framework is developed that accounts for the amount of data and overhead in each packet and the CSI disseminated in the packet. Lower bounds on the peak and average AoI are derived and a greedy protocol that schedules the status updates based on minimizing the instantaneous average AoI is developed. Achievable average AoI is derived for the class of randomized CSI dissemination schedules

Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals

We consider a wireless network with a base station serving multiple traffic streams to different destinations. Packets from each stream arrive to the base station according to a stochastic process and are enqueued in a separate (per stream) queue. The queueing discipline controls which packet within each queue is available for transmission. The base station decides, at every time t, which stream to serve to the corresponding destination. The goal of scheduling decisions is to keep the information at the destinations fresh. Information freshness is captured by the Age of Information (AoI) metric. In this paper, we derive a lower bound on the AoI performance achievable by any given network operating under any queueing discipline. Then, we consider three common queueing disciplines and develop both an Optimal Stationary Randomized policy and a Max-Weight policy under each discipline. Our approach allows us to evaluate the combined impact of the stochastic arrivals, queueing discipline and scheduling policy on AoI. We evaluate the AoI performance both analytically and using simulations. Numerical results show that the performance of the Max-Weight policy is close to the analytical lower bound

The effects of MicroRNA transfections on global patterns of gene expression in ovarian cancer cells are functionally coordinated

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are a class of small RNAs that have been linked to a number of diseases including cancer. The potential application of miRNAs in the diagnostics and therapeutics of ovarian and other cancers is an area of intense interest. A current challenge is the inability to accurately predict the functional consequences of exogenous modulations in the levels of potentially therapeutic miRNAs.</p> <p>Methods</p> <p>In an initial effort to systematically address this issue, we conducted miRNA transfection experiments using two miRNAs (miR-7, miR-128). We monitored the consequent changes in global patterns of gene expression by microarray and quantitative (real-time) polymerase chain reaction. Network analysis of the expression data was used to predict the consequence of each transfection on cellular function and these predictions were experimentally tested.</p> <p>Results</p> <p>While ~20% of the changes in expression patterns of hundreds to thousands of genes could be attributed to direct miRNA-mRNA interactions, the majority of the changes are indirect, involving the downstream consequences of miRNA-mediated changes in regulatory gene expression. The changes in gene expression induced by individual miRNAs are functionally coordinated but distinct between the two miRNAs. MiR-7 transfection into ovarian cancer cells induces changes in cell adhesion and other developmental networks previously associated with epithelial-mesenchymal transitions (EMT) and other processes linked with metastasis. In contrast, miR-128 transfection induces changes in cell cycle control and other processes commonly linked with cellular replication.</p> <p>Conclusions</p> <p>The functionally coordinated patterns of gene expression displayed by different families of miRNAs have the potential to provide clinicians with a strategy to treat cancers from a systems rather than a single gene perspective.</p