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    @Article{OJIOT_2020v6i1n08_Alves,
        title     = {Can You Hear Me? A Metric for Link Asymmetry},
        author    = {Renan C. A. Alves and
                     Cintia B. Margi},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {82--88},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219340603524937},
        urn       = {urn:nbn:de:101:1-2020080219340603524937},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Internet of Things is a networking paradigm aiming to provide computing pervasiveness to our everyday lives. A key component to the Internet of Things is low power networks that gather information from the environment. Low power networks are prone to asymmetric and unidirectional links. Measuring the level of asymmetry and understanding its sources are key steps to successfully deploying sensor networks and the Internet of Things. Our first contribution is a new metric to assess link asymmetry, one which takes into account the instantaneous delivery success probability. Next, we study the influence of four factors on link asymmetry in light of our asymmetry metric, namely, relative distance, output power, relative position, and hardware heterogeneity. With our unique method, we show that all four factors impact link asymmetry.}
    }