No Arabic abstract
In addition to traditional concerns such as throughput and latency, freshness is becoming increasingly important. To stay fresh, applications stream status updates among their components, which can congest the network if the update frequency is too high. Tuning to the right frequency is not trivial, especially in the presence of other flows, when network sharing becomes much more involved. Also, sophisticated tuning logic inevitably complicates the design of the endhost devices. In this paper, we take an alternative approach. Instead of tuning the update frequency at the end-host, we let the endhost send out updates at its own pace and control the freshness within the network. This In-network Freshness Control (IFC) scheme allows the network operator to improve freshness while providing a fine-grained trade-off with throughput. IFC leverages in-network compute resources to filter out obsolete information during transmission of status updates, while queueing other drop-averse traffic separately to provide high throughput. We provide an analytic study of IFC and then implement IFC as Linux kernel modules. Our experiments show that IFC outperforms existing queueing disciplines by improving both throughput (by up to 40%) and freshness (by up to 50%). IFC can easily be combined with existing methods, e.g., BBR and DCTCP, and is effective even in partial deployments.
Wireless Virtual Reality (VR) and Augmented Reality (AR) will contribute to people increasingly working and socializing remotely. However, the VR/AR experience is very susceptible to various delays and timing discrepancies, which can lead to motion sickness and discomfort. This paper models and exploits the existence of multiple paths and redundancy to improve the timing performance of wireless VR communications. We consider Multiple Description Coding (MDC), a scheme where the video stream is encoded in Q streams (Q = 2 in this paper) known as descriptors and delivered independently over multiple paths. We also consider an alternating scheme, that simply switches between the paths. We analyze the full distribution of two relevant metrics: the packet delay and the Peak Age of Information (PAoI), which measures the freshness of the information at the receiver. The results show interesting trade-offs between picture quality, frame rate, and latency: full duplication results in fewer lost frames, but a higher latency than schemes with less redundancy. Even the simple alternating scheme can outperform duplication in terms of PAoI, but MDC can exploit the independent decodability of the descriptors to deliver a basic version of the frames faster, while still getting the full-quality frames with a slightly higher delay.
Age of Information (AoI) has become an important concept in communications, as it allows system designers to measure the freshness of the information available to remote monitoring or control processes. However, its definition tacitly assumes that new information is used at any time, which is not always the case: the instants at which information is collected and used are dependent on a certain query process. We propose a model that accounts for the discrete time nature of many monitoring processes, considering a pull-based communication model in which the freshness of information is only important when the receiver generates a query: if the monitoring process is not using the value, the age of the last update is irrelevant. We then define the Age of Information at Query (QAoI), a more general metric that fits the pull-based scenario, and show how its optimization can lead to very different choices from traditional push-based AoI optimization when using a Packet Erasure Channel (PEC) and with limited link availability. Our results show that QAoI-aware optimization can significantly reduce the average and worst-case perceived age for both periodic and stochastic queries.
Many systems require frequent and regular updates of a certain information. These updates have to be transferred regularly from the source to the destination. We consider scenarios in which an old packet becomes completely obsolete, in the presence of a new packet. In this context, if a new packet arrives at the source while it is transferring a packet, one needs to decide the packet to be dropped. New packet has recent information, but might require more time to transfer. Thus it is not clear as to which packet to be dis- carded, and this is the main focus of the paper. Recently introduced performance metrics, called average age of information (AAoI) and peak age of information (PAoI) of the information available at the destination, are the relevant performance measures. These type of systems do not require storage buffers, of size more than one, at the source queue. We consider single source / multiple sources regularly updating information to a single destination possibly over wireless channels to derive optimal drop policies that optimize the AAoI. We showed that the state independent (static) policies like dropping always the old packets or dropping always the new packets is optimal in many scenarios, among an appropriate set of stationary Markov policies. We consider relevant games when multiple sources compete. In many scenarios, the non-cooperative solution almost minimizes the social objective, the sum of AAoIs of all the sources.
We consider an information updating system where a source produces updates as requested by a transmitter. The transmitter further processes these updates in order to generate $partial$ $updates$, which have smaller information compared to the original updates, to be sent to a receiver. We study the problem of generating partial updates, and finding their corresponding real-valued codeword lengths, in order to minimize the average age experienced by the receiver, while maintaining a desired level of mutual information between the original and partial updates. This problem is NP hard. We relax the problem and develop an alternating minimization based iterative algorithm that generates a pmf for the partial updates, and the corresponding age-optimal real-valued codeword length for each update. We observe that there is a tradeoff between the attained average age and the mutual information between the original and partial updates.
Platooning strategy is an important part of autonomous driving technology. Due to the limited resource of autonomous vehicles in platoons, mobile edge computing (MEC) is usually used to assist vehicles in platoons to obtain useful information, increasing its safety. Specifically, vehicles usually adopt the IEEE 802.11 distributed coordination function (DCF) mechanism to transmit large amount of data to the base station (BS) through vehicle-to-infrastructure (V2I) communications, where the useful information can be extracted by the edge server connected to the BS and then sent back to the vehicles to make correct decisions in time. However, vehicles may be moving on different lanes with different velocities, which incurs the unfair access due to the characteristics of platoons, i.e., vehicles on different lanes transmit different amount of data to the BS when they pass through the coverage of the BS, which also results in the different amount of useful information received by various vehicles. Moreover, age of information (AoI) is an important performance metric to measure the freshness of the data. Large average age of data implies not receiving the useful information in time. It is necessary to design an access scheme to jointly optimize the fairness and data freshness. In this paper, we formulate a joint optimization problem in the MEC-assisted V2I networks and present a multi-objective optimization scheme to solve the problem through adjusting the minimum contention window under the IEEE 802.11 DCF mode according to the velocities of vehicles. The effectiveness of the scheme has been demonstrated by simulation.