Xheal: A localized self-healing algorithm using expanders

We consider the problem of self-healing in reconfigurable networks e.g., peer-to-peer and wireless mesh networks. For such networks under repeated attack by an omniscient adversary, we propose a fully distributed algorithm, Xheal, that maintains good expansion and spectral properties of the network, while keeping the network connected. Moreover, Xheal does this while allowing only low stretch and degree increase per node. The algorithm heals global properties like expansion and stretch while only doing local changes and using only local information. We also provide bounds on the second smallest eigenvalue of the Laplacian which captures key properties such as mixing time, conductance, congestion in routing etc. Xheal has low amortized latency and bandwidth requirements. Our work improves over the self-healing algorithms Forgiving tree [PODC 2008] andForgiving graph [PODC 2009] in that we are able to give guarantees on degree and stretch, while at the same time preserving the expansion and spectral properties of the network.

Edge-preserving self-healing: Keeping network backbones densely connected

Healing algorithms play a crucial part in distributed peer-to-peer networks where failures occur continuously and frequently. Whereas there are approaches for robustness that rely largely on built-in redundancy, we adopt a responsive approach that is more akin to that of biological networks e.g. the brain. The general goal of self-healing distributed graphs is to maintain certain network properties while recovering from failure quickly and making bounded alterations locally. Several self-healing algorithms have been suggested in the recent literature [IPDPS'08, PODC'08, PODC'09, PODC'11]; they heal various network properties while fulfilling competing requirements such as having low degree increase while maintaining connectivity, expansion and low stretch of the network. In this work, we augment the previous algorithms by adding the notion of edge-preserving self-healing which requires the healing algorithm to not delete any edges originally present or adversarialy inserted. This reflects the cost of adding additional edges but more importantly it immediately follows that edge preservation helps maintain any subgraph induced property that is monotonic, in particular important properties such as graph and subgraph densities. Density is an important network property and in certain distributed networks, maintaining it preserves high connectivity among certain subgraphs and backbones. We introduce a general model of self-healing, and introduce xheal+, an edge-preserving version of xheal[PODC'11]. © 2012 IEEE.

The forgiving tree: a self-healing distributed data structure

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that the following process continues for up to n rounds where n is the total number of nodes initially in the network: the adversary deletesan arbitrary node from the network, then the network responds by quickly adding a small number of new edges.

We present a distributed data structure that ensures two key properties. First, the diameter of the network is never more than O(log Delta) times its original diameter, where Delta is the maximum degree of the network initially. We note that for many peer-to-peer systems, Delta is polylogarithmic, so the diameter increase would be a O(loglog n) multiplicative factor. Second, the degree of any node never increases by more than 3 over its original degree. Our data structure is fully distributed, has O(1) latency per round and requires each node to send and receive O(1) messages per round. The data structure requires an initial setup phase that has latency equal to the diameter of the original network, and requires, with high probability, each node v to send O(log n) messages along every edge incident to v. Our approach is orthogonal and complementary to traditional topology-based approaches to defending against attack.

Picking up the Pieces: Self-Healing in reconfigurable networks

We consider the problem of self-healing in networks that are reconfigurable in the sense that they can change their topology during an attack. Our goal is to maintain connectivity in these networks, even in the presence of repeated adversarial node deletion, by carefully adding edges after each attack. We present a new algorithm, DASH, that provably ensures that: 1) the network stays connected even if an adversary deletes up to all nodes in the network; and 2) no node ever increases its degree by more than 2 log n, where n is the number of nodes initially in the network. DASH is fully distributed; adds new edges only among neighbors of deleted nodes; and has average latency and bandwidth costs that are at most logarithmic in n. DASH has these properties irrespective of the topology of the initial network, and is thus orthogonal and complementary to traditional topology- based approaches to defending against attack. We also prove lower-bounds showing that DASH is asymptotically optimal in terms of minimizing maximum degree increase over multiple attacks. Finally, we present empirical results on power-law graphs that show that DASH performs well in practice, and that it significantly outperforms naive algorithms in reducing maximum degree increase.

Algorithms for Self-Healing Networks

Many modern networks are \emph{reconfigurable}, in the sense that the topology of the network can be changed by the nodes in the network. For example, peer-to-peer, wireless and ad-hoc networks are reconfigurable. More generally, many social networks, such as a company's organizational chart; infrastructure networks, such as an airline's transportation network; and biological networks, such as the human brain, are also reconfigurable. Modern reconfigurable networks have a complexity unprecedented in the history of engineering, resembling more a dynamic and evolving living animal rather than a structure of steel designed from a blueprint. Unfortunately, our mathematical and algorithmic tools have not yet developed enough to handle this complexity and fully exploit the flexibility of these networks. We believe that it is no longer possible to build networks that are scalable and never have node failures. Instead, these networks should be able to admit small, and maybe, periodic failures and still recover like skin heals from a cut. This process, where the network can recover itself by maintaining key invariants in response to attack by a powerful adversary is what we call \emph{self-healing}. Here, we present several fast and provably good distributed algorithms for self-healing in reconfigurable dynamic networks. Each of these algorithms have different properties, a different set of gaurantees and limitations. We also discuss future directions and theoretical questions we would like to answer. %in the final dissertation that this document is proposed to lead to.

Self-healing systems and virtual structures

Modern networks are large, highly complex and dynamic. Add to that the mobility of the agents comprising many of these networks. It is difficult or even impossible for such systems to be managed centrally in an efficient manner. It is imperative for such systems to attain a degree of self-management. Self-healing i.e. the capability of a system in a good state to recover to another good state in face of an attack, is desirable for such systems. In this paper, we discuss the self-healing model for dynamic reconfigurable systems. In this model, an omniscient adversary inserts or deletes nodes from a network and the algorithm responds by adding a limited number of edges in order to maintain invariants of the network. We look at some of the results in this model and argue for their applicability and further extensions of the results and the model. We also look at some of the techniques we have used in our earlier work, in particular, we look at the idea of maintaining virtual graphs mapped over the existing network and assert that this may be a useful technique to use in many problem domains.

Elevated Circulation Levels of an Antiangiogenic SERPIN in Patients with Diabetic Microvascular Complications Impair Wound Healing through Suppression of Wnt Signaling

Wound healing, angiogenesis and hair follicle maintenance are often impaired in the skin of diabetic patients, but the pathogenesis has not been well understood. Here, we report that circulation levels of kallistatin, a member of the serine proteinase inhibitor (SERPIN) superfamily with anti-angiogenic activities, were elevated in Type 2 diabetic patients with diabetic vascular complications. To test the hypothesis that elevated kallistatin levels could contribute to a wound healing deficiency via inhibition of Wnt/β-catenin signaling, we generated kallistatin-transgenic (KS-TG) mice. KS-TG mice had reduced cutaneous hair follicle density, microvascular density, and panniculus adiposus layer thickness as well as altered skin microvascular hemodynamics and delayed cutaneous wound healing. Using Wnt reporter mice, our results showed that Wnt/β-catenin signaling is suppressed in dermal endothelium and hair follicles in KS-TG mice. Lithium, a known activator of β-catenin via inhibition of glycogen synthase kinase-3β, reversed the inhibition of Wnt/β-catenin signaling by kallistatin and rescued the wound healing deficiency in KS-TG mice. These observations suggest that elevated circulating anti-angiogenic serpins in diabetic patients may contribute to impaired wound healing through inhibition of Wnt/β-catenin signaling. Activation of Wnt/β-catenin signaling, at a level downstream of Wnt receptors, may ameliorate the wound healing deficiency in diabetic patients.Journal of Investigative Dermatology accepted article preview online, 24 January 2014. doi:10.1038/jid.2014.40.

DEX: Self-Healing Expanders

We present a fully-distributed self-healing algorithm DEX, that maintains a constant degree expander network in a dynamic setting. To the best of our knowledge, our algorithm provides the first efficient distributed construction of expanders - whose expansion properties hold deterministically - that works even under an all-powerful adaptive adversary that controls the dynamic changes to the network (the adversary has unlimited computational power and knowledge of the entire network state, can decide which nodes join and leave and at what time, and knows the past random choices made by the algorithm). Previous distributed expander constructions typically provide only probabilistic guarantees on the network expansion which rapidly degrade in a dynamic setting, in particular, the expansion properties can degrade even more rapidly under adversarial insertions and deletions. Our algorithm provides efficient maintenance and incurs a low overhead per insertion/deletion by an adaptive adversary: only O(log n) rounds and O(log n) messages are needed with high probability (n is the number of nodes currently in the network). The algorithm requires only a constant number of topology changes. Moreover, our algorithm allows for an efficient implementation and maintenance of a distributed hash table (DHT) on top of DEX, with only a constant additional overhead. Our results are a step towards implementing efficient self-healing networks that have guaranteed properties (constant bounded degree and expansion) despite dynamic changes.

Report on the Remedying the Past, Healing for the Future Conference

The signature of fine scale local adaptation in Atlantic salmon revealed from common garden experiments in nature

Understanding the extent, scale and genetic basis of local adaptation is important for conservation and management. Its relevance in salmonids at microgeographic scales, where dispersal (and hence potential gene flow) can be substantial, has however been questioned. Here we compare the fitness of communally-reared offspring of local and foreign Atlantic salmon Salmo salar from adjacent Irish rivers and reciprocal F1 hybrid crosses between them, in the wild ‘home’ environment of the local population. Experimental groups did not differ in wild smolt output but a catastrophic flood event may have limited our ability to detect freshwater performance differences, which were evident in a previous study. Foreign parr exhibited higher, and hybrids intermediate, emigration rates from the natal stream relative to local parr, consistent with genetically-based behavioural differences. Adult return rates were lower for the foreign compared to the local group. Overall lifetime success of foreigners and hybrids relative to locals was estimated at 31% and 40% (mean of both hybrid groups), respectively. The results imply a genetic basis to fitness differences among populations separated by only 50km, driven largely by variation in smolt to adult return rates. Hence even if supplementary stocking programs obtain broodstock from neighbouring rivers, the risk of extrinsic outbreeding depression may be high.

Temporary Places > Community Garden > Peaspark

Temporary Places is a community and art project in North Belfast at two interface areas, New Lodge and Skegoneill/ Glandore. This project (Jan 2013-ongoing) is a collaboration between New Lodge Arts
(lead administrative partner), PS2 (project curators) and Skegoneill & Glandore Common Purpose (community organisation). ‘Temporary Places’ was and still is a project about social and urban regeneration, partly through familiar strategies and activities and partly through more unorthodox, direct and creative interventions. It is an art and community project for all residents and the wider community.

There are several components to the project, but the key and ongoing element is to activate the empty spaces at the Skegoniell / Glandore Interface, by making a 'garden space' of creative activity - now known as Peaspark

DEX: self-healing expanders

The role of LL-37 in periodontal wound healing

Introduction: As a result of chronic inflammation during periodontal disease the junctional epithelium becomes micro-ulcerated. The inflammatory process is mediated by both bacterial and host cell products. Host defence peptides such as defensins, secretory leucocyte protease inhibitor (SLPI) and the sole human cathelicidin, LL-37, are secreted by both periodontal cells and neutrophils into gingival crevicular fluid (GCF). They have the ability to modulate the immune response in periodontitis and are thought to have a potential role in periodontal wound healing. Objectives: The aims of this study were to determine the role of LL-37 in the production of Interleukin (IL)-8, IL-6, hepatocyte growth factor (HGF) and basic-fibroblast growth factor (bFGF) by gingival fibroblasts. The role of LL-37 in modulating total matrix metalloproteinase (MMP) activity and expression of tissue inhibitors of metalloproteinase (TIMP)-1 and -2 by gingival fibroblasts was also investigated. Methods: Primary gingival fibroblasts were co-cultured with concentrations of LL-37 (1, 5 and 10µg/ml) for 24 hours and their supernatants tested for levels of IL-8 and IL-6, HGF, bFGF, TIMP-1 and TIMP-2 by ELISA. Rates of MMP turnover in the supernatants were tested by fluorogenic assay using fluorescence resonance energy transfer (FRET) peptide substrates. Cytotoxicity was measured by MTT assay. Statistical significance was measured using the independent t-test and p<0.05 was considered significant. Results: LL-37 significantly upregulated levels of IL-8, IL-6, HGF, bFGF and TIMP-1 (p<0.05) in a dose-dependent fashion. LL-37 significantly decreased the total MMP activity (p<0.05). None of the LL-37 concentrations tested were cytotoxic to gingival fibroblasts. Conclusion: These results indicate that LL-37 is involved in periodontal wound healing. LL-37 increased levels of proinflammatory cytokines and increased levels of growth factors involved in re-epithelialisation. LL-37 has the ability to regulate remodelling of the periodontium by controlling MMP overactivity both directly and by stimulating production of inhibitors by gingival fibroblasts.

Compact Routing Messages in Self-Healing Trees

Existing compact routing schemes, e.g., Thorup and Zwick [SPAA 2001] and Chechik [PODC 2013], often have no means to tolerate failures, once the system has been setup and started. This paper presents, to our knowledge, the first self-healing compact routing scheme. Besides, our schemes are developed for low memory nodes, i.e., nodes need only O(log2 n) memory, and are thus, compact schemes.
We introduce two algorithms of independent interest: The first is CompactFT, a novel compact version (using only O(log n) local memory) of the self-healing algorithm Forgiving Tree of Hayes et al. [PODC 2008]. The second algorithm (CompactFTZ) combines CompactFT with Thorup-Zwick’s treebased compact routing scheme [SPAA 2001] to produce a fully compact self-healing routing scheme. In the self-healing model, the adversary deletes nodes one at a time with the affected nodes self-healing locally by adding few edges. CompactFT recovers from each attack in only O(1) time and ∆ messages, with only +3 degree increase and O(log∆) graph diameter increase, over any sequence of deletions (∆ is the initial maximum degree).
Additionally, CompactFTZ guarantees delivery of a packet sent from sender s as long as the receiver has not been deleted, with only an additional O(y log ∆) latency, where y is the number of nodes that have been deleted on the path between s and t. If t has been deleted, s gets informed and the packet removed from the network.