Information Resilience through User-Assisted Caching in Disruptive Content-Centric Networks

We investigate an information-resilience scheme in the context of Content-Centric Networks (CCN) for the retrieval of content in disruptive, fragmented networks cases. To resolve and fetch content when the origin is not available due to fragmentation, we exploit content cached both in in-network caches and in end-users’ devices. Initially, we present the required modifications in the CCN architecture to support the proposed resilience scheme. We also present the family of policies that enable the retrieval of cached content and we derive an analytical expression/lower bound of the probability that an information item will disappear from the network (be absorbed) and the time to absorption when the origin of the item is not reachable. Extensive simulations indicate that the proposed resilience scheme is a valid tool for the retrieval of cached content in disruptive scenarios, since it allows the retrieval of content for a long period after the fragmentation of the network and the “disappearance” of the content origin

Pneumococcal Polysaccharide Vaccine Ameliorates Murine Lupus

Current guidelines encourage administering pneumococcal vaccine Prevnar-13 to patients with lupus, but whether such vaccinations affect disease severity is unclear. To address this issue, we treated 3-month-old MRL-lpr mice, that spontaneously develop a lupus-like syndrome, with Prevnar-13 or vehicle control. After 3 months, we quantified circulating anti-Pneumococcal polysaccharide capsule (PPS) antibodies and signs of disease severity, including albuminuria, renal histology and skin severity score. We also compared immunophenotypes and function of T and B cells from treated and untreated animals. Prevnar-13 elicited the formation of anti-pneumococcal IgM and IgG. Prevnar-13 treated animals showed reduced albuminuria, renal histological lesions, and milder dermatitis compared to vehicle-treated controls. Mitigated disease severity was associated with reduced and increased T follicular helper cells (TFH) and T follicular regulatory cells (TFR), respectively, in Prevnar-treated animals. T cells from Prevnar-13 vaccinated mice showed differential cytokine production after aCD3/aCD28 stimulation, with significantly decreased IL-17 and IL-4, and increased IL-10 production compared to non-vaccinated mice. In conclusion, pneumococcal vaccination elicits anti-pneumococcal antibody response and ameliorates disease severity in MRL-lpr mice, which associates with fewer TFH and increased TFR. Together, the data support use of Prevnar vaccination in individuals with SLE

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

The macrophage in HIV-1 infection: From activation to deactivation?

Macrophages play a crucial role in innate and adaptative immunity in response to microorganisms and are an important cellular target during HIV-1 infection. Recently, the heterogeneity of the macrophage population has been highlighted. Classically activated or type 1 macrophages (M1) induced in particular by IFN-γ display a pro-inflammatory profile. The alternatively activated or type 2 macrophages (M2) induced by Th-2 cytokines, such as IL-4 and IL-13 express anti-inflammatory and tissue repair properties. Finally IL-10 has been described as the prototypic cytokine involved in the deactivation of macrophages (dM). Since the capacity of macrophages to support productive HIV-1 infection is known to be modulated by cytokines, this review shows how modulation of macrophage activation by cytokines impacts the capacity to support productive HIV-1 infection. Based on the activation status of macrophages we propose a model starting with M1 classically activated macrophages with accelerated formation of viral reservoirs in a context of Th1 and proinflammatory cytokines. Then IL-4/IL-13 alternatively activated M2 macrophages will enter into the game that will stop the expansion of the HIV-1 reservoir. Finally IL-10 deactivation of macrophages will lead to immune failure observed at the very late stages of the HIV-1 disease

The impact of space division multiplexing on resource allocation: A unified treatment of TDMA,OFDMA and CDMA

Space division multiple access (SDMA) with an antenna array at the transmitter is a promising means for increasing system capacity and supporting rate-demanding services. However, the presence of an antenna array at the physical layer raises significant issues at higher layers. In this paper, we attempt to capture the impact of SDMA on access layer channel allocation, reflected on channel reuse. This impact obtains different twists in TDMA, CDMA and OFDMA due to the different nature of co-channel and cross-channel interference and the different interaction of user spatial channel characteristics with system channels, namely time slots, codes and subcarriers. We consider these access schemes in a generalized unified framework and propose heuristic algorithms for channel allocation, downlink beamforming and transmit power control so as to increase total provisioned system rate and provide QoS to users in the form of minimum rate guarantees. We study the class of greedy algorithms that rely on criteria such as induced or received interference and signal-to-interference ratio (SIR), and a class of SIR balancing algorithms. Results show superior performance for SIR balancing resource allocation and expose the performance benefits of cross-layer design

Optimal Transmission Rate Control Policies in a Wireless Link Under Partial State Information

We consider the problem of PHY layer transmission rate control for maximum throughput on a wireless link over a finite time horizon. For each link state there exists a most advantageous transmission rate for the controller. The controller needs to rely on incomplete link state information in the form of positive acknowledgements (ACKs) and negative acknowledgements (NACKs) for transmitted packets. We cast the problem as a partially observed Markov decision processes (POMDP). We focus on the special case of time-invariant or slowly time varying link quality with two states and two control options. In that case, the optimal control problem is a state estimation one and the optimal strategy is of threshold structure, where the thresholds are certain values of the belief of being in one of the two states. The policy admits a simple interpretation: increase rate when the number of successive ACKs exceeds a threshold, and decrease rate when the number of successive NACKs exceeds a threshold

Carrier assignment algorithms for OFDM-based multi-carrier wireless networks with channel adaptation

We study carrier assignment in a single-cell multiuser OFDM multi-carrier system so as to satisfy user rate requirements with minimal resources. Different users experience different quality in different carriers due to frequency selectivity of users' propagation channels and due to non-co-located user receivers that perceive different interference from neighboring cells across carriers. We study a static instance of the problem, specified by user carrier qualities and rate requirements. Adaptive modulation at the transmitter differentiates carriers for each user. In good quality carriers, the user satisfies per-frame rate requirements with few slots (or equivalently it satisfies its perslot rate requirements with small occupied time slot portion). We study integral and fractional assignment, where a user is assigned to only one or several carriers. Fractional assignment is formulated as a linear programming problem. For integral assignment, we introduce two classes of iterative heuristics that use carrier reassignment to users and user substitution in carriers respectively and may be viewed as resulting from corresponding optimal fractional assignment algorithms. We use Lagrangian relaxation to obtain performance bounds and show that the two classes of heuristics arise from two relaxations. Our approach identifies efficient feasible solutions and is amenable to distributed implementation. © 2008 IEEE

Optimal Control Policies for Power Demand Scheduling in the Smart Grid

We study the problem of minimizing the long-term average power grid operational cost through power demand scheduling. A controller at the operator side receives consumer power demand requests with different power requirements, durations and time flexibilities for their satisfaction. Flexibility is modeled as a deadline by which a demand is to be activated. The cost is a convex function of total power consumption, which reflects the fact that each additional unit of power needed to serve demands is more expensive to provision, as demand load increases. We develop a stochastic model and introduce two online demand scheduling policies. In the first one, the Threshold Postponement (TP), the controller serves a new demand request immediately or postpones it to the end of its deadline, depending on current power consumption. In the second one, the Controlled Release (CR), a new request is activated immediately if power consumption is lower than a threshold, else it is queued. Queued demands are activated when deadlines expire or when consumption drops below the threshold. These policies admit an optimal control with switching curve threshold structure, which involves active and postponed demand. The CR policy is asymptotically optimal as deadlines increase, namely it achieves a lower bound on average cost, and the threshold depends only on active demand. Numerical results validate the benefit of our policies compared to the default one of serving demands upon arrival